UNITED STATES PATENT AND TRADEMARK OFFICE
`
`____________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`____________
`
`Google Inc.
`
`
`
`Petitioners,
`
`v.
`
`Vedanti Systems Limited
`
`Patent Owner.
`
`____________
`
`Case No. IPR2016-00215
`
`Patent No. 7,974,339
`
`____________
`
`
`
`____________
`
`DECLARATION OF Dr. Omid Kia
`
`
`
`
`
`
`
`____________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`____________
`
`Google Inc.
`
`
`
`Petitioners,
`
`v.
`
`Vedanti Systems Limited
`
`Patent Owner.
`
`____________
`
`Case No. IPR2016-00215
`
`Patent No. 7,974,339
`
`____________
`
`
`
`____________
`
`DECLARATION OF Dr. Omid Kia
`
`
`
`
`
`
`
`Dr. Omid Kia Declaration
`
`I, Omid Kia, make this declaration in connection with the proceedings
`
`identified above.
`
`Introduction
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`1.
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`I have been retained by counsel for Vedanti Systems Limited
`
`(“Vedanti”) as a technical expert in connection with the proceedings identified
`
`above. I submit this declaration on behalf of Arendi in the Inter Partes Reviews of
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`United States Patent No. 7,974,339 (“the ‘339 patent”) in Consolidated Case No.
`
`IPR2016-00212.
`
`2.
`
`I base my opinions below on my professional training and experience
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`and my review of documents and materials produced in these Inter Partes reviews.
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`My compensation for this assignment is $450 per hour. My compensation is not
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`dependent on the substance of my opinions or my testimony or the outcome of the
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`above-identified proceedings.
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`Qualifications
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`3. My qualifications for forming the opinions set forth in this report are
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`listed in this section and in Exhibit A attached, which is my curriculum vitae.
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`Exhibit A also includes a list of my publications.
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`4.
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`I am currently the Chief Image Scientist at Northstrat, Inc. (hereinafter
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`referred to as “Northstrat”). In this capacity, I serve as an expert in all of
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`1
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`
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`Northstrat’s imaging initiative along high technology research and development
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`and serve as an expert in all of Northstrat’s activities pertaining to remote sensing,
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`surveillance, and image/signal processing problems.
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`5.
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`Prior to joining Northstrat, I served as the Senior Staff Scientist at ITT
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`Exelis, Space Sciences Division (hereinafter referred to as “ITT Exelis”) in an
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`exact same capacity. ITT Exelis is a leader in Command, Control,
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`Communications, Computers, Intelligence, Surveillance, and Reconnaissance
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`(C4ISR) related products and systems and information and technical services,
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`supplying military, government, and commercial customers in the United States
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`and globally. ITT Exelis is a pure-play aerospace, defense, and information
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`solutions company with strong positions in enduring and emerging global markets,
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`some 20,000 employees, and 2010 revenues of about $6 billion.
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`6.
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`In early 2015 ITT Exelis merged with Harris corporation with
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`complementary capabilities and for further reading please see:
`
`https://www.harris.com/solutions, https://www.harris.com/what-we-
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`do/intelligence-surveillance-and-reconnaissance, https://www.harris.com/solution-
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`grouping/remote-sensing-systems and https://www.harris.com/solution/advanced-
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`analytics.
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`7.
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`A copy of my C.V. is Ex. 2002.
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`2
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`
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`8.
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`In brief, and with particular relevance to the subject matter of this
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`Inter Parties Review, my background and qualifications to be an expert witness in
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`this matter are as follows. I received my Ph.D. degree in Electrical Engineering
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`from the University of Maryland at College Park in 1997. My thesis addressed the
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`compression and processing of images and has content spanning image processing,
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`compression and communication theory and application.
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`9.
`
`Immediately after my graduation, I continued work in media
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`compression and processing at the Compression Group in the Information
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`Technology Laboratory of the National Institutes of Standards and Technology. In
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`this role I continued my research and expanded on similar topics across several
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`media forms. In particular I served as the United States Government ambassador
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`to the MPEG standardization group. I also expanded on my thesis research topic to
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`exploit compressed-domain processing of media for images, video and multimedia
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`content. I worked with engineers who utilized the MPEG standardization body’s
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`source code for performance, quality and testing. There were at least three
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`individuals in my immediate compression group and about 10 individuals working
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`in other companies that contributed to the source code. These individuals were
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`degreed with a Bachelor’s degree in either Electrical Engineering or Computer
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`Science and had direct experience with image processing, compression and
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`communications as it pertains to encoding and decoding of images. At least two
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`3
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`
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`individuals in my immediate group were recent graduates who were performing a
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`cross-country internship from France who were interested in pursuing advanced
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`degrees and part of their education process had to perform actual work to gain
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`relevant experience. These individuals had a bachelor’s degree in either Electrical
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`Engineering or Computer Science with one to two years working experience on
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`compression algorithms that was being studied in my group that included image
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`compression and transmission.
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`10. Since 1999, I have held technical leadership positions in image and
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`signal processing fields for delivery of highly technical solutions to the market. In
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`particular, I have worked with X-ray imaging for medical diagnostic, security
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`scanning, and non-destructive testing purposes.
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`11. From 1999 to 2001, I served as the Chief Technical Officer at
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`IMACOM, a medical imaging company that manufactured and sold Fluoroscopy
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`and Radiography systems. From 2002 to 2003 I served as the president at Sigma
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`Vision, a company that specialized in radiography for veterinary, security, and
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`non-destructive testing. I worked with hardware and software engineers that
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`provided technical support in development and maintaining of the imaging
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`machines produced by the company. A large part of the system was to provide
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`real-time processing, display and transmission of images within the system and
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`across system boundaries to systems such as Radiological Information Systems
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`4
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`
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`(RIS) and Hospital Information Systems (HIS). Specifically interface to RIS
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`systems were accomplished by the Picture Archiving and Communication System
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`(PACS). We performed research and development in various compression and
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`transmission options that included a well accepted practice of transmitting Motion
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`JPEG video where series of frames in a video is compressed by a JPEG image
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`compression technique. The engineers working with me had bachelor’s degree in
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`Electrical Engineering and Computer Science with hands on experience in various
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`aspects of the system some of which was at least one to two year equivalent
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`experience in image processing, compression and communications.
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`12. From 2004 to 2009, I served as the Chief Scientist and Director of
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`Digital X-Ray Development at Imaging Sciences International, Inc. (hereinafter
`
`referred to as “ISII”), a company that marketed a broad scope of imaging and
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`workflow solutions for the dental market. Since 2009 I have served at ITT Exelis
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`as a senior scientist responsible for government contracts as Chief Engineer and
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`Chief Scientist. Also at ITT Exelis, served as one of the leading experts in image
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`and video compression.
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`13.
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`In these capacities, I have worked on many aspects of digital imaging
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`for X-Rays, optical, hyperspectral, radiofrequency in active or passive modes,
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`including algorithm development, software development, hardware development,
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`receptor development, and system design. I have also implemented image and
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`5
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`
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`video compression baselines for various products. In every case where
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`compression was involved, I had to perform an image quality analysis to determine
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`the appropriate level of compression or mitigation of the anticipated induced loss
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`in the compression. Moreover, I had to also perform rate analysis to determine the
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`level of appropriate compression to achieve in order to meet the available channel
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`requirements ranging from dial-up modem to satellite communication.
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`Information Considered in Forming Opinion
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`14.
`
`I have reviewed the Inter Partes Review pleadings for the above
`
`referenced proceedings including ‘‘339 Patent, U.S. Patent No. 4,791,486
`
`(“Spriggs”) U.S. Patent No. 5,225,904 (“Golin”), U.S. Patent No. 6,529,634
`
`(“Thyagarajan”), “Spatially Adaptive Subsampling of Image Sequences”
`
`(“Belfor”) and Dr. Grindon’s Declarations. I have relied on my own knowledge
`
`and experience as well as published documents in forming my opinions.
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`Person of Ordinary Skill in the Art
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`15.
`
`In my opinion, a person of ordinary skill in the art pertaining to the
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`'339 patent at the relevant date discussed below would have at least a technical
`
`degree in Electrical Engineering, Computer Science or equivalent curriculum with
`
`coursework in image processing and at least one year of hands on experience with
`
`compression and communication techniques.
`
`6
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`
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`16. Alternatively, the person of ordinary skill may have earned a degree in
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`Electrical Engineering, Computer Science or equivalent curriculum with
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`coursework in compression and communication and at least one year of hands on
`
`experience in imaging.
`
`17. Despite the focus of the invention on reducing bandwidth
`
`requirements, i.e, data reduction, Petitioner’s statement of one of ordinary skill is
`
`so expansive it encompasses persons with no coursework and no experience in data
`
`compression.
`
`‘339 Patent
`18. Coincident with the explosive growth of the Internet through the
`
`utilization of embedded multimedia in the World Wide Web, the invention of the
`
`‘339 patent addressed a demanding and important telecommunication requirement
`
`for image and video streaming. The concept of motion estimation had already
`
`formed the basis for video encoding by achieving high compression rates by
`
`simply removing redundancies associated with moving objects in the scene. With
`
`increased memory, processing and communication improvements a new era of
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`streaming media was ushered in with video streaming being the most valuable
`
`entity.
`
`19. To address one aspect of managing the transmission requirements for
`
`high throughput and low latency, the inventors of the ’339 patent came up with a
`
`7
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`
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`solution of applying a pixel selection process to regions generated by an analysis
`
`process performed on the pixels of a video image.
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`20. By separately using both of these processes, the resulting system
`
`allows for optimization of the regions and, in addition, a pixel selection process
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`that “allows random, sequenced, or other suitable processes to be used to select and
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`locate pixels with optimized regions.” ’339 patent, Ex. 1001, 7:7-9. Combining
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`frame analysis to generate regions and pixel selection for each region as taught in
`
`the patent has been used to significantly improve the quality of video transmission
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`and reception over the Internet.
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`Terminology
`21. The term “data” is used in the ’339 patent in the computing and
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`communications sense of the word.
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`22. Thus, as would be understood by one of ordinary skill in the art, data
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`refers to “digital information” or “bits that can be made available for storage,
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`transmission and/or interpretation.”
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`Spriggs
`23. The patent of Spriggs discloses a method for image transmission
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`employing a process for determining when to subdivide picture areas for reducing
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`the amount of data needed for transmitting an image. Ex. 1005 at Abstract
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`(“Spriggs”). Spriggs begins with an image and then determines whether to
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`8
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`
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`subdivide the image into smaller picture areas based on how well an estimated
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`version of the data compares to the actual pixel data for a given area.
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`24.
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`If the estimated version is within a threshold of the actual pixel data,
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`then the image is not subdivided but if the estimated version is above a threshold
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`when compared to the actual values, the image is divided both horizontally and
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`vertically into quadrants.
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`25. The estimated version is determined using the four corner pixel values
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`for each area. Spriggs interpolates between the four corner pixel values to create
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`an estimate for each addressable pixel within the area. The process continues until
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`all areas of the image that are not subdivided are analyzed to see if they need to be
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`subdivided.
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`26. Spriggs produces an encoded data stream that can be decoded by a
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`receiver by transmitting division codes and also transmitting the sample values
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`used in the estimation/interpolation process for making the subdivision decisions.
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`27. Fig. 4 of Spriggs shows how the variably-sized areas are created in
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`more detail. Spriggs begins by generating the addresses of the four corner points
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`for an image. Ex. 1005 at Fig. 4. Next, the corner addresses are pushed onto a
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`memory stack. The corresponding corner samples are then transmitted to the
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`receiver.
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`9
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`
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`28. Spriggs then performs an algorithm to determine whether to subdivide
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`the image. Spriggs performs this methodology by pulling the four corner addresses
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`off the stack and then generates interpolated samples for the frame based upon the
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`four corner samples that correspond to the four corner addresses. Ex. 1005, 2:27-
`
`35. The interpolated version of the image is compared with the actual samples to
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`determine if the estimated and actual samples differ by less than a threshold
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`criterion. Id., 2:36-46. If the threshold is met then a division code of “0” is
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`transmitted. Id., 3: 2-4. The “0” indicates that the image has not been subdivided
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`and that a region has been generated.
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`10
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`
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`29.
`
`If the comparison is not within the margin of the threshold criteria, the
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`frame is subdivided into quadrants. Ex. 1005, 3:4-7. Five addresses, the address at
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`the center of the region being divided and the center of each of the four sides of the
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`region, are determined as represented below by the bolded values (EFGHI). Id.,
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`3:7-9.
`
`
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`30. These five center pixel values will be used as corner values for
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`evaluating the quadrants. Because the frame is subdivided, a subdivision code of
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`“1” is transmitted. Ex. 1005, 3:4-5.
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`31. Then, the sample values for the five addresses are transmitted as
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`shown and described with respect to Fig. 6. Ex. 1005, 3:63-68.
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`11
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`
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`
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`32. The top of Fig. 6 of Spriggs shows an exemplary image frame that has
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`undergone the described encoding process and the bottom of Fig. 6 shows the
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`exemplary output stream for the image frame, which is transmitted to a receiver.
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`Id. The output stream consists of sample data (SA, SB, etc.) shown in the middle
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`column and division codes (i.e. 0,1) shown in the left column.
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`33. The bracketed data in the right column are for informational purposes
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`and are not transmitted data. Ex. 1005, 3:65-68. These bracketed corner addresses
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`are used to show the associated corner addresses that relate to the division codes of
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`‘0’ and ‘1’.
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`12
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`
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`34. The top of Fig. 6 shows a number of regions including regions defined
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`by their corner points. The regions defined by corner points (AFEI), (FBIG),
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`(IGHD) are the upper left, upper right and lower right quadrants of the image.
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`Additionally, there are several smaller regions defined by corner points (EPOS)
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`(PKSQ) (OSJR) (SQRN) (KINL) (JNCM) AND (NLMH).
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`35. The method for creating the data stream of Fig. 6 begins as described
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`above for Fig. 4 with the four corner sample values for the image (SA,SB,SC,SD)
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`being transmitted. These values are interpolated to generate an interpolated block
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`and the block of interpolated values is compared to the actual sample values for the
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`image.
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`36.
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`In the example shown in Fig. 6, the threshold is not met and the image
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`is subdivided. Because of the subdivision, a “1” is transmitted. Id. The
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`methodology then determines the five center pixel values “SE, SF, SG, SH and
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`SI”. These will be available for use as corners for the four sub-regions that are
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`being created. The specification of previously specified corner points with the
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`newly defined center points allows specification of corner points for newly divided
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`sub-regions. The methodology then looks at the top left quadrant using the corner
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`pixel values SA, SF, SE, and SI from the stack to construct interpolated values for
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`the quadrant. The methodology compares the interpolated pixel values for the
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`quadrant to the actual pixel values for the quadrant and in this example, it is
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`13
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`
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`determined that the interpolated pixels meet the threshold criterion and a “0” is
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`transmitted, indicating that this region (defined by corners AFEI) does not need to
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`undergo any further subdivisions. Based upon having issued the “region data” of
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`“0”, no further examination of the pixel data of this region is required or performed
`
`in the coding process.
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`37. The process continues with the upper right quadrant having pixel
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`values SF, SB, SI, SG, which are taken off of the stack. These four corner pixel
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`values are interpolated to define interpolated pixel values for the quadrant, which
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`are compared to the actual pixel values of the quadrant and again the threshold is
`
`met so a “0” is transmitted. No further examination of the pixel data of newly-
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`created region FBIG takes place in the coding process.
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`38. The encoding process continues by evaluating the lower left quadrant
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`composed of corner pixel values “SE, SI, SC, SH” that are read off of the stack.
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`The interpolated quadrant values when compared to the actual pixel values for the
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`quadrant do not meet the threshold and therefore, a “1” is generated for
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`transmission and the quadrant is further subdivided into smaller sized regions. The
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`quadrant is divided horizontally and vertically and, as shown in Figs. 4 and 6, the
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`five center values SJ, SK, SL, SM, SN are transmitted to the receiver. The upper
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`left sub-quadrant defined by corner points (E,K,J,N) is interpolated by corner pixel
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`values “SE, SK, SJ, SN” and compared to the actual sample values for that region
`
`14
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`
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`and the methodology determines that this quadrant should be subdivided and
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`therefore, a “1” is generated for transmission. Again, the five center values are
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`transmitted namely, SO, SP, SQ, SR, and SS.
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`39. As can be seen in Fig. 6, after the final subdivision of the lower left
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`quadrant occurs causing transmission of pixel values SO, SP, SQ, SR, and SS with
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`no additional subdivisions occur for the regions defined by corner addresses
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`(EPOS), (PKSQ), (OSJR), (SQRN), (KINL), (JNCM), (NLMH), and (IGHD). In
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`fact, no corresponding pixel values need be transmitted for these regions and Figs.
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`4 and 6 show only a set of 8 consecutive “0”s being transmitted to the receiver.
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`Thus, for each of these regions only the subdivision code “0” must be sent. No
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`further examination of the pixel data of these newly-created regions take place in
`
`the coding process.
`
`Golin
`40. Golin discloses a video compression system. Each region of a video
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`frame is custom encoded. Ex. 1006, 4:68-5:1. Golin teaches a roughness estimator
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`for detecting edges in the pixel data and if such edges or “roughness” make the
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`encoding process unacceptable, the region is split horizontally or vertically. Ex.
`
`20. Petitioner relies on Golin for its disclosure of a roughness estimator. Golin
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`describes fill methods, such as DPCM, that are quite distinct from pixel selection.
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`15
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`
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`‘339 Patent includes both an Analysis System and a Pixel Selection System in
`Contrast to the Spriggs System that only includes an Analysis System
`41. Embodiments of the ’339 patent disclose a system and method that
`
`uses data optimization for reducing data transmission requirements. Ex. 1001,
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`3:13-14. The data transmission system includes a frame analysis system and a
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`pixel selection system. The frame analysis system analyzes the data within the
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`frames to divide the frame into a plurality of regions defined by region data. Id.,
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`3:51- 4:11. Not until the region data has been determined for a region and been
`
`received by the pixel selection system can the pixel selection system operate on
`
`that region to select pixel values for that region. The region needs to be known and
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`received for the pixel selection process to take place. Id. The pixel selection
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`system receives the region data and uses the region data in selecting one or more
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`pixels from within the region to transmit to the receiver for reconstruction of the
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`image. Id., 4:12-14.
`
`42.
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`In contrast, the Spriggs patent includes only an analysis system for
`
`analyzing whether to split an area using quad-tree decomposition. Spriggs does not
`
`include the required pixel selection system.
`
`43. Spriggs recursively looks at an area of an image to see if the area
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`needs to be subdivided or if corner pixel values will be sufficient to represent the
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`area. If the corner pixel values are not sufficient to represent the data in the area
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`when interpolated, the area is subdivided and five center values (center of the
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`16
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`
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`block being subdivided and centers of each of its four sides) are determined and
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`transmitted as shown by Spriggs.
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`44.
`
` Each of these pixel values will be used in the corners of the quadrant
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`regions being formed. These pixel values are data that is transmitted to the receiver
`
`to be used by a decoder for reconstructing the image and are shared among many
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`possible regions.
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`45.
`
` Additionally, a division code (“0” or “1”) is transmitted to the
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`receiver indicative of whether or not the area is subdivided.
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`46. A region of the image in Spriggs as shown below in Fig. 6 is only
`
`finalized when a “0” code has been generated. The code is transmitted to the
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`receiver not to any pixel selection system. Thus, given the lack of any process at
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`the transmitter that has access to the region data for selecting pixels, Spriggs does
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`not allow for a pixel selection process based on the region data.
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`17
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`
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`47. Spriggs fails to teach a pixel selection system that receives region data
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`and that generates pixel values for each region based on the region data as required
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`by the independent claims. Spriggs simply performs analysis on the image to
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`determine whether an image should be subdivided horizontally and vertically and
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`transmits corresponding division codes. These division codes are never received
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`by a pixel selection system and the division codes are not used for selecting pixel
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`values for the region.
`
`48.
`
` The initial pixel values that are transmitted in the output data stream
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`consist of the four corner values for the image, e.g. SA, SB, SC, SD. Since the
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`regions have not yet been generated, these values are not the result of any pixel
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`18
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`
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`selection for a region. These values are transmitted before the regions are even
`
`known.
`
`49. The coding process of Spriggs goes on to generate the regions. In the
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`example, regions AFEI, FBIG, JNCM and IGHD become the regions in which
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`each of A, B, C and D are located. These regions are not known when the values
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`have been transmitted for A, B, C and D and in particular JNCM is not known until
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`after at least two subdivision cycles later. As the coding process continues, sets of
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`five center pixels may be determined whenever there is a split. As was the case for
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`the initial pixels, these pixels do not receive an associated region until a “0”
`
`division code is issued.
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`50. Accordingly, Spriggs fails to teach generating one set of pixel data for
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`each region based on received region data/optimized matrix data.
`
`51. The lower half of Fig. 6 of Spriggs demonstrates a data transmission
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`stream that is sent to the receiver for the image shown in the upper half of Fig. 6.
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`The transmission stream does not present a set of pixel data for any of the regions.
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`The left column represents the division codes/region data, the middle column
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`represents the transmitted sample values and the right column, which is not
`
`transmitted are helpful comments indicating the corresponding corners of the block
`
`associated with the individual division codes of 1 or 0.
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`19
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`
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`52. As can be seen in Fig. 6, corresponding pixel data is not generated for
`
`each region based upon the division codes/region data. For example, regions
`
`defined by corners (AFEI) region 1, (FBIG) region 2, (EPOS) region 3, (PKSQ)
`
`region 4, (OSJR) region 5, (SQRN) region 6, (KINL) region 7, (JNCM) region 8,
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`(NLMH) region 9 and (IGHD) region 10, are indicated by a representative “0” for
`
`the division code shown in the first column. Once the “0” is transmitted, the
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`coding process moves onto a next region. No pixel selection process for the region
`
`is triggered. Spriggs entirely misses the approach of the ’339 patent, which
`
`combined an analysis to generate region data with a process that receives the
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`region data and selects pixels on the basis of the region data.
`
`53. The recursive process of Fig. 4 in Spriggs is the entire coding process
`
`wherein the encoding process results in an output stream as shown in Fig. 6 of
`
`Spriggs. No further processing at the encoder occurs after the recursive process of
`
`Fig. 4 has completed. The output produces a single output of data that includes
`
`division codes and the pixel data, as corner pixel values, which were used to
`
`generate the division codes based on a desirable encoding error criteria for the
`
`regions. Neither the division codes nor the pixel data are used in a further “pixel
`
`selection” process. There is no process disclosed or suggested by Spriggs, which
`
`receives the region data and generates pixel data for a region.
`
`20
`
`
`
`54.
`
`In Fig. 4, the corner pixel values can be found among the pixel values
`
`transmitted during the production of the regions by the analysis system. These
`
`values are determined during the region generating process. There is no subsequent
`
`pixel selection process.
`
`55. The recursive flowchart of Fig. 4 determines when to subdivide
`
`regions into sub-regions and provides pixel values for transmission. However, this
`
`is a singular process and the pixel values are transmitted first before a region is
`
`finally identified by a ‘0’ division code.
`
`56. As shown in Fig. 6, SA through SI are transmitted before region AFEI
`
`is determined by the ‘0’ division code. The process of the pixel selection system is
`
`completely missing from Spriggs and the Petitioner merely repurposes its analysis
`
`for the “analysis system” suggesting that it likewise covers the “pixel selection
`
`system.”
`
`57.
`
`In Fig. 4, the “0” and “1” division codes are transmitted to the
`
`receiver. The “1”s and “0”s in the data stream can be used by the receiver to
`
`determine how to reconstruct the image at the receiver. The division codes are not
`
`received and used in a process for selecting pixel data in the transmitter.
`
`58.
`
`In Spriggs, upon each iteration of its recursive process as exemplified
`
`in Fig. 4, the process always begins with the corner pixel values and addresses of
`
`the corner pixels of the initial block. The process performs an analysis function to
`
`21
`
`
`
`determine if the block should be split and be recorded in the division codes. These
`
`division codes are immediately transmitted as they are generated as seen in Fig. 4.
`
`The region data are never received by a pixel selection system in Spriggs encoder
`
`that generates one set of pixel data for each region forming a new set of data for
`
`transmission as required by claim 1. The division codes are transmitted in a
`
`transmission stream to the receiver.
`
`59. The example of corner pixels given in the Petition is “SA, SB, SC,
`
`SD”. Each of these is the corner of a different region in Fig. 6. Spriggs’ coding
`
`process begins with these pixels. They are certainly not selected “based on”
`
`optimized matrix data. They are generated and transmitted before Spriggs’ coding
`
`process makes its first decision.
`
`60. Spriggs never selects between two or more sets of pixel data, which
`
`would require a decision process that is clearly lacking in Spriggs.
`
`61.
`
`In Fig. 6, the set SA, SB, SC, SD does not form a region. SA is in
`
`region AFEI, SB is in a different region FBIG and SC is in yet another region
`
`JNCM.
`
`Belfor
`
`62. Belfor reduces the data representing an image by performing a
`
`subsampling process where “[b]y discarding a part of the pixels, the image can be
`
`transmitted more efficiently.” Ex. 1007, 1. Fixed subsampling is compared with
`
`22
`
`
`
`spatially adaptive subsampling. Improved storage and transmission performance is
`
`shown for spatially adaptive subsampling relative to fixed subsampling.
`
`63.
`
`“In a spatially adaptive subsampling scheme, the image is subdivided
`
`into square blocks, and each block is represented by a specific spatial sampling
`
`lattice.” Ex. 1007, 1. The scheme addresses high detail and low detail areas of an
`
`image by using a dense sampling lattice in high detail blocks and a sparse sampling
`
`lattice with few pixels in a low detail block. Accommodating the varying detail
`
`through variable subsampling in conjunction with a representative lattice structure
`
`provides the improvement over using a fixed sampling and lattice structure.
`
`64. Block sizes considered in Belfor refer to the dimensions of the block.
`
`Belfor illustrates a block size with dimensions of 8 pixels by 8 pixels. Ex. 1007, 4.
`
`Furthermore, Belfor notes, “The number of possible modes is affected by the block
`
`size because for decreasing block size, the number of possible sampling lattices
`
`within the block decreases as well.” Id. at 4. Because the number of pixels in the
`
`block makes it possible to use a certain number of subsampling lattices. For a
`
`given block size, Belfor provides an associated set of modes from which to choose,
`
`each mode having a specific subsampling lattice. Id. at 4. For the use of
`
`sophisticated interpolation in decoding, the set of modes for a given block size is
`
`preferably hierarchical. Id. at 4. Hierarchical means mode n+1 is always a subset
`
`23
`
`
`
`of mode n, as shown in Fig. 4. Id. at 4.
`
`65. The system of Belfor, as shown in Fig. 5, runs each block through a
`
`pre-filtering step. This is followed by a subsampling step for each of the modes in
`
`
`
`the set.
`
`66. The subsampled image for each mode at each block is evaluated for
`
`quality by an error computation module. Then the mode allocation module makes
`
`the determination as to which mode is the best representative mode to be allocated
`
`to each individual block. After the modes have been allocated, in other words – a
`
`
`
`24
`
`
`
`mode has been assigned to each block – the data for the image is transmitted
`
`through the channel. The data would include the mode assignment for each block
`
`and the pixels remaining after applying the respective subsampling to each of the
`
`blocks.
`
`67. Belfor further discusses the complexities involved in allocating the
`
`modes to the blocks. According to Belfor, “The mode allocation is of great
`
`significance as it influences the output quality considerably.” Ex. 1007, 4. In the
`
`simplest allocation approach, only two modes are used. To produce a desired
`
`output bit rate, a fraction of the blocks will be assigned one mode and the
`
`remaining fraction of the blocks will be assigned the other mode. The fractions are
`
`chosen so that the total bits approximate the desired bit rate. To implement this
`
`approach, the less dense mode is applied to all of the blocks. The distortion or
`
`error computation is determined for each block. Then the blocks with the highest
`
`computed distortion will be assigned the denser mode in an effort to increase total
`
`number of bits while decreasing the largest amounts of distortion. It is the aim of
`
`the process to still keep the total number of bits below a desired amount while
`
`decreasing the distortion.
`
`68. Belfor seeks to describe a mode allocation algorithm that can be used
`
`with any number of modes. Ex. 1007, 5. But increasing the modes to more than
`
`two will produce a pair of equations that cannot be uniquely solved. Id. at 5. It is
`
`25
`
`
`
`necessary that the modes produce a rate-distortion curve that is convex as shown in
`
`Fig. 6. Id. at 5. In other words, as the bit rate ratio (remaining bits in the lattice
`
`divided by total bits in the block) increases moving to the right in Fig. 6, the
`
`distortion D is reduced. Id. at 5.
`
`
`
`This convexity is in line with the theoretical definition of rate distortion theory in
`
`that every added bit used to represent an image should meth
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