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`8 Levi Eshkol Street
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`Only complete this section when filing an application by reference under 35 U.S.C. 1 INC) and 37 CFR 1.57ta). Do not complete this section if
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`Request Not to Publish. I hereby request that the attached application not be published under
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`subject of an application filed in another country, or under a multilateral international agreement, that requires
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`I laims benefit of provisional
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`P253239
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`14547148
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`908343
`' 011-03-15
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`A. Priority Document Exchange (PDX1- Unless box A in subsection 2 (opt-out of authorization) is checked, the
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`Applicant Information:
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`Providing assignment information in this section does not substitute for compliance with any requirement of part 3 of Title 37 of CFR
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`5 Montebello Road
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`OPTIMIZED IMAGE DELIVERY OVER LIMITED BANDWIDTH COMMUNICATION
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`W
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`Isaac Levanon
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`Yonatan Lavi
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`Priority Claims/Related Applications
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`This application is a continuation of and claims priority to US. Patent Application Serial
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`No. 14/970,526, filed December 15 , 2015, entitled OPTIMIZED IMAGE DELIVERY OVER
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`LIMITED BANDWIDTH COMMUNICATION CHANNELS, now allowed; which is a
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`continuation of and claims priority to US. Patent Application Serial No. 14/547,148, filed
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`November 19, 2014, entitled OPTIMIZED IMAGE DELIVERY OVER LIMITED
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`BANDWIDTH COMMUNICATION CHANNELS, now US. Patent No. 9,253,239; which is a
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`continuation of and claims priority to US. Patent Application Serial No. 13/027,929, filed
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`February 15, 2011, entitled OPTIMIZED IMAGE DELIVERY OVER LIMITED
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`BANDWIDTH COMMUNICATION CHANNELS, now US. Patent No. 8,924,506; which is a
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`continuation in part of and claims priority to US. Patent Application Serial No. 12/619,643 filed
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`on November 16, 2009, entitled OPTIMIZED IMAGE DELIVERY OVER LIMITED
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`BANDWIDTH COMMUNICATION CHANNELS, now US. Patent No. 7,908,343; which is a
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`continuation of and claims priority to US. Patent Application Serial No. 10/035,987 filed on
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`December 24, 2001 and entitled OPTIMIZED IMAGE DELIVERY OVER LIMITED
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`BANDWIDTH COMMUNICATION CHANNELS, now US. Patent No. 7,644,131; which
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`claims the benefit under 35 U.S.C. §119(e) of US. Provisional Application Nos. 60/258,488,
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`60/258,489, 60/258,465, 60/258,468, 60/258,466, and 60/258,467, all filed December 27, 2000.
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`The present application is also related to application serial number 10/035,981 entitled SYSTEM
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`AND METHODS FOR NETWORK IMAGE DELIVERY WITH DYNAMIC VIEWING
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`FRUSTUM OPTIMIZED FOR LIMITED BANDWIDTH COMMUNICATION CHANNELS,
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`Levanon er al., filed on December 24, 2001, now US. Patent No. 7,139,794, issued on
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`November 21, 2006, which is assigned to the Assignee of the present Application. The
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`disclosures of all of the foregoing patent documents are incorporated herein by reference as if
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`fully set forth herein, including Figures, Claims, and Tables.
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`Field
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`The disclosure is related to network based, image distribution systems and, in particular,
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`to a system and methods for efficiently selecting and distributing image parcels through a
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`narrowband or otherwise limited bandwidth communications channel to support presentation of
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`high—resolution images subject to dynamic viewing frustums.
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`B ackground
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`The Internet and or other network systems may provide a unique opportunity to transmit
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`for example complex images, typically large scale bit—maps, particularly those approaching
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`photo—realistic levels, over large area and or distances. In common application, the images may
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`be geographic, topographic, and or other highly detailed maps. The data storage requirements
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`and often proprietary nature of such images could be such that conventional interests may be to
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`transfer the images on an as—needed basis.
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`In conventional fixed—site applications, the image data may be transferred over a
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`relatively high—bandwidth network to client computer systems that in turn, may render the
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`image. Client systems may typically implement a local image navigation system to provide zoom
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`and or pan functions based on user interaction. As well recognized problem with such
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`conventional systems could be that full resolution image presentation may be subject to the
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`inherent transfer latency of the network. Different conventional systems have been proposed to
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`reduce the latency affect by transmitting the image in highly compressed formats that support
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`progressive resolution build—up of the image within the current client field of view. Using a
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`transform compressed image transfer function increases the field of the image that can be
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`transferred over a fixed bandwidth network in unit time. Progressive image resolution
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`transmission, typically using a differential resolution method, permits an approximate image to
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`be quickly presented with image details being continuously added over time.
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`Tzou, in U.S. Pat. No. 4,698,689, describes a two—dimensional data transform system
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`that supports transmission of differential coefficients to represent an image. Subsequent
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`transmitted coefficient sets are progressively accumulated with prior transmitted sets to provide a
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`succeedingly refined image. The inverse—transform function performed by the client computer is,
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`however, highly compute intensive. In order to simplify the transform implementation and
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`further reduce the latency of presenting any portion of an approximate image, images are sub—
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`divided into a regular array. This enables the inverse—transform function on the client, which is
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`time—critical, to deal with substantially smaller coefficient data sets. The array size in Tzou is
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`fixed, which leads to progressively larger coefficient data sets as the detail level of the image
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`increases. Consequently, there is an inherently increasing latency in resolving finer levels of
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`detail.
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`An image visualization system proposed by Yap et al., U.S. Pat. No. 6,182,114,
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`overcomes some of the foregoing problems. The Yap et al. system also employs a progressive
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`encoding transform to compress the image transfer stream. The transform also operates on a
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`subdivided image, but the division is indexed to the encoding level of the transform. The
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`encoded transform coefficient data sets are, therefore, of constant size, which supports a modest
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`improvement in the algorithmic performance of the inverse transform operation required on the
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`client.
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`Yap et al. adds utilization of client image panning or other image pointing input
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`information to support a foveation—based operator to influence the retrieval order of the
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`subdivided image blocks. This two—dimensional navigation information is used to identify a
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`foveal region that is presumed to be the gaze point of a client system user. The foveation
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`operator defines the corresponding image block as the center point of an ordered retrieval of
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`coefficient sets representing a variable resolution image. The gaze point image block represents
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`the area of highest image resolution, with resolution reduction as a function of distance from the
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`gaze point determined by the foveation operator. This technique thus progressively builds image
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`resolution at the gaze point and succeedingly outward based on a relatively compute intensive
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`function. Shifts in the gaze point can be responded to with relative speed by preferentially
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`retrieving coefficient sets at and near the new foveal region.
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`Significant problems remain in permitting the convenient and effective use of complex
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`images by many different types of client systems, even with the improvements provided by the
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`various conventional systems. In particular, the implementation of conventional image
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`visualization systems is generally unworkable for smaller, often dedicated or embedded, clients
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`where use of image visualization would clearly be beneficial. Conventional approaches
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`effectively presume that client systems have an excess of computing performance, memory and
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`storage. Small clients, however, typically have restricted performance processors with possibly
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`no dedicated floating—point support, little ge