LUND UNIVERSITY
`
`Atomic physics
`
`Lund University Publications
`Institutional Repository of Lund University
`Found at http://www.lu.se
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`LUP
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`
`
`This is an author produced version of a paper published in
`Optics Express
`
`This paper has been peer-reviewed but does not include the
`final publisher proof-corrections or journal pagination.
`
`Citation for the published paper:
`Sandsten, J; Wcibring, Potter; Edncr, Hans ct a1.
`”Real—time gas—correlation imaging employing thermal background radiation”
`Optics Express
`2000, V01. 6:4, pp. 92—103
`
`http.'//dx.doi.org/10. 1364/OE. 6. 000092
`
`Access to the published version may require subscription.
`Published with permission from:
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`FLIR Systems, Inc.
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`

`Real-time gas-correlation imaging employing
`thermal background radiation
`
`Jonas Sandsten, Petter Weibring, Hans Edner and Sune Svanberg
`Department ofPl/tysics, Lundlnstitute ofTec/qnology, P. 0. Box 118, 5—22] 00 Lund, Sweden
`Jonas.Sandvten@]jzsik.[ti/Lye
`
`http://www—atom. fysik. lth. re
`
`Abstract: Real-time imaging of gas leaks was demonstrated using an IR
`camera employing outdoor
`thermal background radiation. Ammonia,
`ethylene and methane detection was demonstrated in the spectral region 7-
`13 um.
`Imaging was accomplished using an optical
`filter and a gas-
`correlation cell matching the absorption band of the gas. When two gases,
`such as ammonia and ethylene, are absorbing in the same wavelength region
`it is possible to isolate one for display by using gas-correlation multispectral
`imaging. Results from a field test on a leaking gas tanker are presented as
`QuickTime movies. A detection limit of 200 ppm X meter for ammonia was
`accomplished in this setup when the temperature difference between the
`background and the gas was 18 K and the frame rate was 15 Hz.
`@2000 Optical Society of America
`OCIS codes: (040.3060) Detectors,
`infrared; (110.3080) Infrared imaging; (280.1120) Air
`pollution monitoring; (300.6340) Spectroscopy, infrared
`
`>'
`
`9°
`
`10.
`
`References and links
`1.
`T.J. Kulp, P.E. Powers and R. Kennedy, “Remote imaging of controlled gas releases using active and passive
`infrared imaging systems,” in Infrared Technology and Applications XXIII, B.F. Andresen, M. Strojnik Scholl,
`eds, Proc. SPIE 3061, 269-278 (1997).
`S.-A. Ljungberg, T.J. Kulp and T.G. McRae, “State-of the-art and firture plans for IR imaging of gaseous
`fiigitive emission,” in Thermosense XIX, R.N. Wurzbach, D.D. Burleigh, eds, Proc. SPIE 3056, 2-19 (1997).
`C. Allander, P. Carlsson, B. Hallén, B. Ljungqvist and O. Norlander, “Thermocamera a macroscopic method for
`the study of pollution with nitrous oxide in operating theatres”, Acta Anaesth. Scand. 25, 21-24 (1981).
`T.G. McRae and T.J. Kulp, “Backscatter absorption gas imaging: a new technique for gas visualization,” Appl.
`Opt. 32, 4037-4050 (1993).
`I. Sandsten, H. Edner and S. Svanberg, “Gas imaging by infrared gas-correlation spectrometry,” Opt. Lett. 21,
`1945-1947 (1996), http://www-atomiysiklth. se/JonasSandsten/GasC orrelationlmaginghtm.
`T.V. Ward and H.H. Zwick, “Gas cell correlation spectrometer: GASPEC,” Appl. Opt. 14, 2896-2904 (1975).
`HS. Lee and H.H. Zwick, “Gas filter correlation instrument for the remote sensing of gas leaks,” Rev. Sci. Instr.
`56, 1812-1819 (1985).
`H. Edner, S. Svanberg, L. Unéus and W. Wendt, “Gas-correlation lidar,” Opt. Lett. 9, 493-495 (1984).
`PS. Andersson, S. Montan and S. Svanberg, “Multi-spectral system for medical fluorescence imaging,” IEEE J.
`Quant. Electr. QE-23, 1798-1805 (1987).
`LS. Rothman, C.P. Rinsland, A. Goldman, S.T. Massie, D.P. Edwards, J.-M. Flaud, A. Perrin, C. Camy-Peyret,
`V. Dana, J.-Y. Mandin, I. Schroeder, A. McCann, R.R. Gamache, R.B. Wattsin, K. Yoshino, K.V. Chance,
`KW. Juck, LR. Brown, V. Nemtchechin, P. Varanasi, The HITRAN molecular spectroscopic database: 1996
`edition, I. Quant. Spectrosc. Radiat. Transfer 60, 665-710 (1998).
`M.L. Polak, IL. Hall and KC. Herr, “Passive Fourier-transform infrared spectroscopy of chemical plumes: an
`algoritm for quantitative interpretation and real-time background removal,” Appl. Opt. 34, 5406-5412 (1995).
`PL. Hanst, QASofi '96, Database and quantitative analysis program for measurements of gases, Infrared
`Analysis Inc., Anaheim, Ca, 1996.
`GRAMS/32, Array basic programming language, Galactic Industries Corp.
`
`11.
`
`12.
`
`13.
`
`1. Introduction
`
`Real-time gas imaging is of great interest in many contexts [1,2]. Inspection of leaks from
`chemical
`installations, petrochemical plants,
`tank farms or pipelines has economical,
`
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`Received January 03, 2000; Revised February 08, 2000
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`environmental and security aspects. Easily deployable surveillance techniques for assessing
`sites of accidents involving gas tankers or trains are desirable for public safety considerations.
`In the indoor working environment, gas flow monitoring around air inlets and outlets,
`extraction hoods or local ventilation units is useful for optimizing the construction and
`adjustment of installations. Emissions of geophysical origin (volcanoes, geothermal
`installations or mines) as well as natural emanations of greenhouse gases from agriculture,
`swamps etc., are also interesting to assess. Useful spectroscopic absorption features of the
`molecules of interest occur in the visible or infrared spectral regions. The vibrational-
`rotational bands in the fundamental infrared region, 3700 cm'1 to 500 cm'l, are particularly
`suitable for sensitive gas detection. While active monitoring of gases using lidar techniques is
`possible,
`range and imaging capabilities are limited. A passive system using ambient
`background radiation is more attractive for real-time imaging.
`In the present paper we
`demonstrate, as we believe for the first
`time, practical gas passive imaging with gas
`identification using a sensitive infrared camera combined with optical filter and gas cell
`correlation techniques. The method relies on simultaneous multi-spectral
`imaging and
`computer processing of the data. Results from a field test on a leaking gas tanker are
`presented.
`Previous IR work has involved the use of heat blankets or IR illuminators to enhance the
`
`[3]. Scanning laser irradiation has been employed for close-range
`natural radiation level
`applications [4]. Recently, we demonstrated selective gas imaging using gas-correlation
`spectrometry for automatic gas identification, in a working environment scene employing
`added IR radiation [5]. The gas-correlation principle was originally introduced for line-of-
`sight monitoring and has later also been used in combination with lidar [6-8].
`The virtue of the gas-correlation technique is the holistic discrimination between spectral
`frequencies with specific gas absorption and transparent areas, which is obtained by
`comparing a direct recording to a recording through an optically thick gas absorption cell. In
`our previous work we extended the principle to imaging by employing a technique for
`simultaneous multi-spectral recording using a specially designed split-mirror Cassegrainian
`telescope, allowing up to 4 geometrically similar but spectrally differently filtered images to
`be simultaneously recorded in the four quadrants of the 2D detector [9]. Two of the images
`were used, one direct image and one, which was filtered through a gas cell. Gas flows in an
`indoor working environment were visualized, but the IR camera employed, an Agema
`THV900 SW unit, had a sensitivity limit calling for the slight heating of the background scene
`using a 1000 W IR illuminator equipped with a reflector. Our present work has overcome
`some of the previous limitation by utilizing a more sensitive Agema THV900 LW system and
`more powerful
`image processing techniques to actually allow ambient thermal outdoor
`background radiation as the only illumination in real-time recordings at 15 frames/s. The
`special virtue of the gas-correlation technique is that it allows the separation of gases which
`have overlapping spectra (e.g. ammonia and ethylene). A proper IR wavelength window
`where the gases of interest absorb is chosen by a bandpass filter, but the high-resolution
`"holistic" filtering is performed by the optically thick correlation gas. The lay-out of the
`present paper is as follows. Detailed spectral considerations are presented in the next section,
`including a method to estimate gas concentration >< length, followed by a description in Sect. 3
`of the experimental arrangements used in the field measurements. Our data processing and
`dynamic gas flow presentation are discussed in Sect. 4, followed by a section presenting our
`results. Finally, we conclude with a discussion section with suggestions for technology
`improvements and future work.
`
`2. Spectral consideration
`
`By using remote infrared detection techniques most species, except homonuclear diatomic
`species, can be detected and quantified due to their unique infrared spectral properties in the
`wavelength region 3-13 um [10]. In order to choose the optimal wavelength region for passive
`detection several factors have to be taken into account. The most important factors are
`atmospheric transmission (i.e. water and carbon dioxide absorption), background radiation
`
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`flux and the integrated oscillator strengths of the absorption lines of the species of interest.
`Fig.
`1 shows a typical atmospheric transmission in the IR region, together with the spectral
`radiances of five blackbody radiators with normal background temperatures ranging from 273
`K to 313 K. As can be seen, water and carbon dioxide absorption block part of the spectrum
`or limit the effective range of optical measurements. The region from 8-13 um contains more
`water bands than the 3-4 um region, but the background radiation is more than 30 times
`higher at normal terrestrial temperatures, i.e. 300 K. The strength of the absorption band of
`many species of interest is also considerable higher in the 8-13 um region. Even though water
`interference in the 7-8.5 um (1400-1200 cm'l) wavelength region is severely affecting the
`signals, it is possible to utilize this region for measurements of methane, employing the gas-
`correlation technique.
`N20 co2
`H20
`
`Transmittance
`
`2500
`
`3000
`
` 2000
`
`
`
`
`
`
`
`
`0.8
`
`a:
`3
`0.6 g
`In
`a:
`L
`E
`E
`0.4 g
`E
`
`0.2
`
`Wavenumber(cm'1)
`
`
`
`
`
`
`
`
`50
`
`g 40
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`
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`N
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`E 20
`E
`E
`'5’a 10
`U)
`
`0
`
`500
`
`1000
`
`1500
`
`2000
`
`2500
`
`3000
`
`Wavenumber ( cm'1 )
`
`Fig. 1. Top: Atmosphere transmittance through 300 meters of urban air [12]. Bottom: Spectral
`radiance of five blackbody radiators (left axis) and the normalized spectral response curve of
`our IR camera (right axis).
`
`Passive techniques using natural thermal background radiation for gas detection is very
`suitable around 1000 cm'1 due to maximum spectral radiance for such temperatures and a
`greatly transparent atmosphere. Gases that absorb infrared radiation in this atmospheric
`window are affecting the sun-earth radiative balance, which in turn is affecting the
`temperature on earth. IR cameras manufactured for use in the atmospheric window around
`1000 cm'l, are by definition also very suitable for visualization of greenhouse gas
`concentration gradients. Varying thermal background, reflectance or emittance over the image
`are compensated when using the imaging gas-correlation technique.
`
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`Taken into account these spectral considerations we choose an Agema Thermovision 900
`LW infrared camera, which has a low noise-equivalent temperature difference, NEAT, of 80
`mK. The relative spectral response, which is at its maximum at 900 cm'1 (11 pm), is also
`shown in Fig. 1. together with the spectral radiances of five blackbody radiators.
`Computer based convolution simulations for the spectral response of the camera system,
`comprised of the detector, camera optics, filters and gas-correlation cells, were performed.
`The simulation enabled determination of the properties of the whole optical transmission
`system except the Cassegrainian telescope which was considered not to influence the spectral
`response notably. Also profiling and determination of different filter types were possible. To
`achieve an optimal sensitivity is a question of balancing the use of narrow bandpass filters,
`optimized on strong spectral features, to yield a high contrast response, against the overall
`photon transmission in the system. Static noise in the detector requires the photon flux to be
`over a certain level to achieve a good signal-to-noise ratio. Furthermore, a bandpass filter is in
`itself radiating more than a short- or long-wavelength-pass filter. Therefore, by varying the
`wavelength region and its width, maximizing the ratio between the integrated total absorption
`of the gas of interest and the integrated total optical transmission of the system, an optimal
`filter profile can be selected.
`
`1
`
`
`
`Filter profiles
`
`
`
`
`0.8 7
`
`a:
`g 0.6 7
`53
`-‘=
`E
`3
`E 0.4 7
`
`0.2 7
`
`
`
`7 0.8
`
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`
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`a
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`
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`
`7 0
`1500
`
`~ 7
`
`7
`
`.
`
`
`
`0 7
`700
`
`800
`
`1000
`
`1200
`
`1300
`
`1400
`
`.
`900
`
`7
`1100
`
`Wavenumber (cm'1)
`
`Fig. 2. The normalized spectral response of the IR camera (dark blue curve) is convoluted with
`the transmittance of two different gas cell window materials and optical filter profiles, yielding
`two regions of relative response (black curves). The gases are both shown in absorbance at
`concentrations of 200 ppm x In
`
`As a result of the simulations, a best effort filter for detection of ammonia and ethylene in
`the 8-13 um wavelength region is a long-wavelength-pass filter (cut-on at 9.2 pm) with 80 %
`transmission and a best effort filter for detection of methane is a broad bandpass filter (half
`power points at 7 um and 8.5 pm) with 60 % transmission.
`For the gas-correlation cell windows, several materials with transmission in the 2-13 um
`wavelength region were considered. We choose ZnSe for measurements of species with
`absorption around 10 um, and CaF2 for species around 8 pm; see Fig. 2. The ZnSe window
`surfaces were antireflection coated to reduce the reflection loss due to a high index of
`refraction, yielding more than 90 % transmission with a maximum of 99 % at 10.6 um.
`In Fig. 2 the transmittances of the discussed elements are shown together with the
`convoluted total response (black curves). FT-IR recorded spectra of 200 ppm X meters of
`ammonia and methane are shown in units of gas absorbance as red and orange lines,
`respectively [12].
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`2.1 Gas concentration calibration
`
`Gas concentration calibration for ammonia was performed by integrating the relative
`transmittance of the system over wavenumbers from 700 to 1100 cm'l, with increasing gas
`concentrations, and then dividing the decreasing integrated relative transmittance with the
`integrated relative transmittance without gas. This procedure is primarily described for the
`case of direct absorption measurements. In the process the databases HITRAN 1996, QASoft
`’96 and the software GRAMS/32 were used [10.12.13]. Fig. 3 shows convoluted spectra at
`two different concentration levels. The absorption line wing contribution influence was taken
`into account by using HITRAN composite spectra.
`1 ,
`
`0.8 ,
`
`0.6 ,
`
`0.4 ,
`
`0.2 ,
`
`0
`
`700
`
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`750
`
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`800
`
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`
`i
`900
`
`i
`950
`
`i
`1000
`
`i
`1050
`
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`
`Wavenumber (cm'1)
`
`
`
`
`Transmittance
`
`Transmittance
`
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`
`mar
`
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`
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`
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`
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`
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`1100
`
`Fig. 3. A. Ammonia transmittance spectrum at a concentration of 400 ppm x m, convoluted
`with the system response. The black envelope integrated transmittance (no gas) divided by the
`integrated transmittance under the gas spectrum corresponds to the transmittance of the system.
`B. Ammonia transmittance spectrum at a concentration of 4000 ppm x m, convoluted with the
`system response.
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`Fig. 4 shows the integrated transmittance for different concentrations of ammonia,
`calculated from several convoluted spectra. This calculation was first performed for a very
`large temperature difference between the background and the gas. However, in a practical
`situation with a thermal background, the self-radiance from the gas has to be taken into
`account. The gas will selectively radiate at the absorption lines with an intensity of [(l-
`Transmittance) >< BG], where BG is the intensity of a blackbody radiator at the gas temperature
`TG. This will be seen as a higher effective transmittance of the gas, and this effect can be
`calculated by adding the emitted intensity of the gas at temperature TG to the transmitted
`intensity of the background at temperature TB. The resulting corrected transmittance as a
`function of the concentration at the prevailing experimental value of AT = 18 K (AT = TB —
`TG) is shown in Fig. 4. We did not expect to find a Beer-Lambertian like relationship between
`gas transmittance and concentration since we have not monochromatic light, but a wavelength
`distribution requiring an extension of the law obtained by integration over wavenumbers. At
`small concentration levels we find a near linear relationship while going towards higher
`concentration levels the function becomes asymptotic. It should be noted that AT has to be
`known for a correct calibration and that for AT = 0 no absorption will be observed due to the
`fact that the absorption and emission cancel out.
`
`A
`
`B
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
` Integratedtransmittance
`
`
`
`
`0
`
`2000
`
`4000
`
`6000
`
`8000
`
`10000
`
`12000
`
`14000
`
`16000
`
`18000
`
`20000
`
`External ammonia gas concentration (ppm x m)
`
`Fig. 4. Resulting calibrated ammonia gas concentration. Integrating the black envelopes in Fig.
`3 corresponds to a transmittance value of one. Arrows A and B correspond to the integrated
`transmittance of the spectra in Fig. 3.
`
`The theoretically calculated integrated transmittance values for different AT were
`validated in a laboratory set-up. A 8 X 8 cm2 aluminum plate, coated with a high-emissivity
`black paint and coupled to a Peltier element, was used as the background target. In front of
`this a 20 mm thick cell filled with 20000 ppm X m ammonia gas was placed. The gas cell was
`held at a constant temperature of 294 K, while the temperature of the background target was
`varied. The results for 6 different values of AT are displayed in Fig. 5 together with the
`theoretical curve, showing good agreement. Please note, that for negative values of AT, a
`relative transmittance larger than I can be obtained. The temperature of the background
`surface was measured using a non-contact
`thermometer with laser aiming (Mikron®
`Instrument, model MlOlHT) with an accuracy of l K. The laboratory set-up was also used to
`determine the offset of the signal levels detected by the camera. This offset is mostly due to
`thermal emissions from the camera itself, the filter and the telescope. By plotting the detected
`
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`signal from the aluminum plate versus the band emittance from a blackbody at the measured
`temperature, the offset could be calculated.
`
`12,
`
`Relative
`
`transmittance
`
`-15
`
`-10
`
`-5
`
`0
`
`5
`
`10
`
`15
`
`20
`
`25
`
`30
`
`35
`
`40
`
`AT
`
`Fig. 5. Theoretically calculated relative transmittance through 20000 ppm x m ammonia gas as
`a filnction ofAT : TB 7 Tc, with Tc, : 294 K. The results of an experimental verification are
`inserted with error bars in the figure
`
`3. Field experiment arrangements
`
`Field experiments with the techniques developed were performed at the training station of the
`Malmo Fire Brigade. This site is located in southern Sweden and the measurements were
`performed in the month of September during mostly sunny conditions with an ambient air
`temperature of 18-21 0C and a relative humidity of 50%. Rather windy conditions with gusts
`up to 12 m/s prevailed. The measurement scenario and optical arrangements are illustrated in
`Fig. 6. A burnt-out rusty gas tank trailer was used as the target, forming a background with a
`surface temperature of 30-40 0C and an emissivity of 0.9. Gas bottles with ammonia, ethylene
`and methane were connected through long tubes attached to the trailer, simulating leaks. This
`set-up enabled controlled releases of one or several gases with different flow rates at or near
`the ambient air temperature.
`The optical equipment was placed at a distance of 20 m from the trailer. Two images of
`the object were formed at the same time on the IR-sensitive camera with the Cassegrainian
`split-mirror telescope, with a total receiving area of 2 X 10 cm2. The all-reflective optics of the
`telescope are comprised of two primary spherical aluminum mirrors and a secondary spherical
`aluminum mirror. The aluminum with Mng coating has 96% reflectance over the spectral
`region of the camera. The positions of the primary mirrors are adjustable by fine threaded
`screws and focusing is done by translating the secondary mirror along the common optical
`axis. The Agema Thermovision 900 LW camera is using a Stirling-cooled MCT signal-
`processing-in-the-element (SPRITE) detector and a scanner which, line by line, scans the
`object. Timing circuits create an image of the line scans resulting in a resolution of 272 X 136
`pixels. The image is split by the Cassegrainian telescope into two regions of 136 X 136 pixels
`each.
`
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`14 February 2000 / V01. 6, N0. 4/ OPTICS EXPRESS 98
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`

`
`
`Gas cell
`
`|:|
`
`Dual image
`Cassegrainian
`telescope
`
`CCD
`
`IR camera with
`spectral filtering
`
`PC with real-time
`image processing
`
`
`
`«at
`
`.
`
`Fig. 6. Measurement scenario and optical arrangements.
`
`The camera was equipped with suitable interference filters, used to isolate a small spectral
`region containing absorption features of the gas to be studied, as discussed earlier. The
`interference filters were mounted on a filter wheel in front of the detector inside the camera.
`
`In front of the telescope a 20 mm gas cell makes an additional filtering on one of the images.
`The gas cell was filled with an appropriate amount of a certain gas, making the cell essentially
`opaque at the stronger absorption lines. The two images thus produced can be used to extract a
`pure gas image and eliminate differences in the thermal background radiation as well as the
`interference by other gases or particles. A simultaneous recording of the scene in the visible
`spectral region was performed with a CCD camera mounted close to the telescope.
`
`4. Data processing and dynamic presentation
`
`The IR camera is connected to a PC with an Imaging Technology frame grabber and a fast
`SCSI hard disk, allowing real-time recordings of 12-bit, 272 X 136 pixels, at 15 frames/s.
`Image processing was performed on a PC with the Agema Irwin Research software and
`Matlab with the Image Processing Toolbox. After processing,
`the gas images could be
`overlaid on a normal
`image of the scene recorded with the CCD camera. The image
`processing was performed according to the following scheme:
`0 Two images A and B are captured at the same time using the Cassegrainian telescope,
`the IR camera and the frame grabber.
`A — image of the infrared scene from one of the telescope openings.
`B — image of the same scene with a gas cell in front of the other opening.
`0 The appropriate offset is subtracted from the images.
`0 An error (normalization) image, E, from the Cassegrainian telescope is created to
`handle imperfections such as asymmetrical vignetting, and stray-light from the two
`openings, E = A0 / B0. E is recorded with no gas present in the scene.
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`

`o The images are digitally overlapped by translation and optimization within a region of
`interest containing the gas, and subsequent image processing is restricted to this
`region.
`0 A gas-correlation image is calculated, G = A / B / E.
`o On the result
`image, G a two-dimensional spatial median filter with a 3x3
`neighborhood averaging is performed to reduce the
`strong spike-like noise
`components (salt-and-pepper noise).
`0 The concentration levels (of ammonia) are set by threshold values obtained from
`simulations in GRAMS/32 and calculations with Excel as described in Sect. 2.1.
`
`0 Finally, the gas-correlation image is overlaid onto a visible image of the background
`and the resulting 15 frames/s movie is presented in Matlab.
`
`For presentation purposes QuickTime movies are created in which we electronically
`zoom into the gas leakage and compress the gas-correlation resulting movies for fast access
`on Internet. An additional advantage of the normalization procedure described above is that
`gas concentration evaluations for the case of gas-correlation imaging can be handled in a
`similar way as described for the direct absorption case in Fig. 4 and 5.
`
`5. Measurements and results
`
`Results from the measurements at the Malmo Fire Brigade gas training station are presented
`in three PC image processing modes; all of them based on the two-dimensional spectroscopic
`gas-correlation image processing. In Sect. 5.1 binary images of ammonia, ethylene and
`methane overlaid on a visible image of the gas tanker background are presented. In Sect. 5.2
`the ammonia gas is presented together with a color-scale of the concentration overlaid onto
`the visible background image, and in Sect. 5.3 the ammonia gas is shown together with the
`spectrally interfering ethylene gas, but the ammonia gas is distinguished from the ethylene gas
`and colored red with the gas-correlation image processing mode.
`
`5.1 Visualization ofammonia, ethylene anal methane leaks
`
`To the left in Fig. 7 we show one or more gases (green colored) which absorb infrared light
`from the background in the spectral region defined by the filter, cell window material and
`camera response. The right-hand image is the result of gas-correlation image processing and
`we are thus certain that the gas is ammonia (red colored) and not interfering gases or varying
`background reflectances, emissivities or temperatures. The gas correlation cell, with a length
`of 20 mm, was filled with ammonia at a pressure of 1 atm., resulting in 20000 ppm X meters
`with fully saturated spectral lines. It was not possible to detect external ammonia gas through
`the gas cell as expected.
`
`
`
`Fig. 7. (2 MB) Movie of an ammonia leak, left: by direct absorption and right: by gas-
`correlation. Binary gas images merged with visible images. Measurement conditions: Time
`14:30, Air temperature 18 °C, Surface temperature 36 °C, Relative humidity 48 %, Gas flow
`100 l/min, ZnSe gas cell with ammonia at 1 atm., Filter: Spectrogon LP9200.
`
`In Fig. 8 we show leaking ethylene with the same method as for ammonia above. Again,
`we are certain that it is ethylene in the red-colored image due to gas correlation with an
`
`#19020 - $15.00 US
`(C) 2000 OSA
`
`Received January 03, 2000; Revised February 08, 2000
`14 February 2000 / V01. 6, N0. 4/ OPTICS EXPRESS 100
`
`FLIR Systems, Inc.
`1019-00010
`
`

`

`ethylene gas cell. Notice that we have to somewhat sacrifice signal-to-noise ratio if we want
`to gain this information.
`
`
`
`Fig. 8. (1.7 MB) Movie of an ethylene leak, left: by direct absorption and right: by gas
`correlation Measurement conditions: Time 15:10, Air temperature 20 °C, Surface temperature
`38 °C, Relative humidity 50 %, Gas flow 10 l/min, ZnSe gas cell with ethylene at 1 atm., Filter:
`Spectrogon LP9200
`
`In Fig. 9 methane is visualized by direct absorption in the region from 7-8.5 um which is
`very sensitive to water vapor, see Fig. 12. Water vapor interferes spectrally with methane gas
`but this problem is alleviated by gas correlation; the gas itself is the perfect spectral filter for
`discrimination against other gases. The lower sensitivity of the camera in this region gives a
`slightly lower signal-to-noise ratio.
`
`
`
`Fig. 9. (1.8 MB) Movie of a methane leak, left: by direct absorption and right: by gas
`correlation. Measurement conditions: Time 15:40, Air temperature 22 °C, Surface temperature
`40 °C, Relative humidity 50 %, Gas flow 90 l/min, Can gas cell with methane 1 atm., Filter:
`Spectrogon BBP7040-8500
`
`5.2 Ammonia gas concentration visualized with a concentration color-scale
`
`2700 A
`
`EX
`
`300
`
`2100 e
`E
`1500 .5
`E
`900 §C
`
`8
`
`Fig. 10. (1.8 MB) Movie of an ammonia leak, color-scale concentration image. Measurement
`conditions: Time 14:30, Air temperature 18 °C, Surface temperature 36 °C, Relative humidity
`48 %, Gas flow 10-100 l/min, ZnSe gas cell with ammonia at 1 atm., Filter: Spectrogon
`LP9200.
`
`#19020 - $15.00 US
`(C) 2000 OSA
`
`Received January 03, 2000; Revised February 08, 2000
`14 February 2000 / V01. 6, N0. 4/ OPTICS EXPRESS 101
`
`FLIR Systems, Inc.
`1019-00011
`
`

`

`The spatial two-dimensional concentration >< length of ammonia, with an increasing flow
`from the first to the last image,
`is shown in Fig. 10. The concentration calculation was
`performed according to the method described in Sect. 2.1. This sequence of images was used
`to determine a detection limit of 200 ppm X m in the present set-up.
`
`5.3 Spectrally interfering ammonia and ethylene separated by gas correlation
`
`
`
`Fig. 1 1. (1.9 MB) Simultaneous imaging of ammonia and ethylene leaks showing the isolation
`of the ammonia flow using the gas-correlation technique. Measurement conditions: Time
`17:25, Air temperature 192 °C, Surface temperature 315 °C, Relative humidity 50 %,
`Ammonia gas flow 15 l/min, Ethylene gas flow 10 l/min, ZnSe gas cell with ammonia 1 atm.,
`Filter: Spectrogon LP9200.
`
`In Fig. 11 the result of gas-correlation with ammonia and spectrally interfering ethylene is
`shown. The image on the left hand shows both ammonia (upper gas) and ethylene (lower gas)
`leaks in direct absorption and the image on the right hand is the result after gas correlation,
`showing ammonia only. We observe that a slight cross talk from ethylene is visible in some of
`the resulting ammonia frames; this is due to a few interfering spectral lines; see Fig. 12.
`
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`
`Fig. 12. Absorbance spectra of ammonia, ethylene and methane (200 ppm x m). Water vapor is
`interfering with methane. IR camera system relative response (black curves).
`
`6. Discussion and conclusions
`
`Real-time gas visualization using IR thermal background radiation and gas correlation is
`demonstrated, as we believe, for the first time. Live sequences of ammonia, ethylene and
`methane leaks are shown and gas
`separation for
`spectrally overlapping species
`is
`demonstrated. As shown in the paper there is a possibility to quantify the emissions. However,
`
`#19020 - $15.00 US
`(C) 2000 OSA
`
`Received January 03, 2000; Revised February 08, 2000
`14 February 2000 / V01. 6, N0. 4/ OPTICS EXPRESS 102
`
`FLIR Systems, Inc.
`1019-00012
`
`

`

`an accurate knowledge of the temperature difference between the gas and the background is
`then necessary. Calibrated measurements also put a higher demand on control of the camera
`and telescope temperatures. Present sensitivities are in the range of 200 ppm X meters for
`ammonia (AT = 18 K) at a frame rate of 15 Hz, with an estimated sensitivity improvement of a
`factor 10 if moderate temporal and spatial averaging is performed. This detection limit is
`presently limited by imperfections in the telescope construction, resulting in image errors and
`varying offset problems. These effects could here be handled by recording an image without
`the gas present in the scene. With a better construction of the telescope, this procedure should
`not be necessary and the two sub-images, with and without the gas correlation cell, could be
`used to fully compensate for a varying background. Potentially, several gases could be
`monitored with a camera sensitive in the 8-14 pm region. The emerging QWIP (Quantu