Chapter 10: Image Modeling

1. Chapter 10: Image Modeling

2. 10.2 Approaches to Simulation 10.2.1 Physical Models Figure 10.1 Simulation facility and synthetic image produced using physical models. (Courtesy of Itek Corporation.)

3. 10.2.1 Physical Models Figure 10.1 Simulation facility and synthetic image produced using physical models (Courtesy of Itek Corporation.) (con’t).

4. 10.2.2 Fully Computerized Models Figure 10.2 Diagram of conceptual data flow and interaction mechanisms in a generic SIG model.

5. 10.2.2 Fully Computerized Models Figure 10.3 LWIR synthetic image of targets in forested area. (Image courtesy of the Army Night Vision Lab.)

6. 10.2.2 Fully Computerized Models Figure 10.4 Synthetic LWIR image of a tank. (Image courtesty of Michigan Technological University, Keweenaw Research Center.)

7. 10.2.2 Fully Computerized Models Figure 10.5 Synthetic image of a ship on modeled ocean. (Image courtesy of ERIM.) Figure 10.6 Synthetic LWIR image showing a helicopter over simulated water. (Image courtesy of Georgia Tech Research Institute.)

8. 10.3 Modeling Example Figure 10.7 Wire frame of an object used in the SIG process. The object is produced using CAD software and material types are assigned to each facet during the construction process.

9. 10.3 Modeling Example Figure 10.8 Illustration of the ray-tracing process for a simple framing camera. To generate an N x M radiance array, rays are traced from the focal point through each point through each pixel center in an N x M image plane.

10. 10.3 Modeling Example Figure 10.9 Sun shadow history.

11. 10.3 Modeling Example Figure 10.10 Rays are cast into the hemisphere above the plane of the target pixel to compute the shape factor for use in the thermodynamic modeling of radiational exchange and in the radiometric image formation model.

12. 10.3 Modeling Example Figure 10.11 The final synthetic image is obtained by convolving the radiance image (indicated by the pixel heights in the figure) with the point spread function (PSF) of the system and sampling the resulting image.

13. 10.3 Modeling Example (a) (b) (c) (e) (d) Figure 10.12 DIRSIG LWIR radiance image: (a) and several debug images, (b) transmission along line of site, (C) path radiance, (d) target emissivity, and (e) target material map.

14. 10.3 Modeling Example (a) (b) Figure 10.13 A final DIRSIG image (a) and debug images showing later stages of the image chain, (b) radiance image, (c) radiance image with noise effects, and (d) radiance image with MTF effects. Final image includes noise, MTF, and sampling effects.

15. 10.3 Modeling Example (c) (d) Figure 10.13 (con’t) A final DIRSIG image (a) and debug images showing later stages of the image chain, (b) radiance image, (c) radiance image with noise effects, and (d) radiance image with MTF effects. Final image includes noise, MTF, and sampling effects.

16. 10.3 Modeling Example Figure 10.14 A false-color synthetic scene produced by DIRSIG showing texture effects.

17. 10.3.2 Application of SIG models Figure 10.15 Contrast-enhanced blue spectral band DIRSIG line scanner image of a uniform Lambertian ground model. Plane is flying north (up) with the sun east (right). The brightness variations in the image are strictly due to atmospheric transmission and scattering effects.

18. 10.3.2 Application of SIG models Figure 10.16 Color IR version of ASAS images from three flight lines showing combined effects of atmospheric and bidirectional reflectance variation. (Image courtesy of NASA Goddard.)

19. 10.3.2 Application of SIG models (a) (b) Figure 10.17 LWIR DIRSIG image showing airfield at different wind speeds.

20. 10.3.2 Application of SIG models 100% specular 10% specular Figure 10.18 Sample image subsections produced by DIRSIG displaying the effects of specularity . Note the “double shadow” in the image modeled with 100% specular concrete.

21. 10.3.2 Application of SIG models (b) (c) (a) Figure 10.19 DIRSIG images showing sensor modeling: (a) frame camera, (b) line scanner model including V/H and tangent errors, and (c) line scanner model with aircraft roll included.

22. 10.3.2 Application of SIG models Figure 10.20 A synthetic sunset produced by DIRSIG. The effect is possible due to extensive spectral modeling DIRSIG incorporates with the help of MODTRAN.

23. 10.5 References Berk, A., Bernstein, L.S., & Robertson, D.C. (1989). “MODTRAN: a moderate resolution model for LOWTRAN 7.” GL-TR-89-0122, Spectral Sciences Inc., Burlington, MA. Cathcart, J.M., Faust, N.L., Sheffer, A.D. Jr., & Rodriquez, L.J. (1993). “Background clutter models for scene simulation.” Proceedings of the SPIE, Vol. 1938, No. 37, pp. 325-336. DCS Corporation (1991). “AIRSIM thermal signature prediction and analysis tool model assumptions and analytical foundations.” DCS Technical Note 9090-002-001. Foley, J.D., vanDam, A., Feiner, S.K., & Hughes, J.F. (1990). Computing Graphics: Principles and Practices, 2d ed., Addison-Wesley, Reading, MA. Francis, J., Maver, L., & Schott, J.R. (1993). “Comparison of physically and computer generated imagery.” Proceedings of the SPIE, Vol. 1904, pp. 20-23. Haruyama, S., & Barsky, B.A. (1984). Using stochastic modeling for texture generation. IEEE Computer Graphics and Applications, Vol. 4, pp. 7-19. Johnson, K.R., Curran, A.R., & Gondo, T.G. (1993). “Development of a signature super code,” Proceedings of the SPIE, Vol. 1938, No. 36, pp. 317-304. Kornfeld, G.H., & Penn, J. (1993). “Various FLIR sensor effects applied to synthetic thermal imagery.” Proceedings of the SPIE, Vol. 38, No. 39, pp. 350-367. Mason, J.E., Schott, J.R., & Rankin-Parobek, D. (1994). “Validation analysis of the thermal and radiometric integrity of RIT’s synthetic image generation model, DIRSIG.” Proceedings SPIE, Vol. 2223, pp. 474-487. Mason, J.E., Schott, J.R., Salvaggio, C., & Sirianni, J.D. (1994). “Validation of contrast and phenomenology in the digital imaging and remote sensing (DIRS) lab’s image generation (DIRSIG) model.” Proceedings of SPIE, Vol. 2269, pp. 622-633.

24. 10.5 References Maver, L., & Scarff, L. (1993). “Multispectral image simulation.” Proceedings of the SPIE, Vol. 1904, pp. 144-160. Pentland, A.P. (1984). Fractal-based description of natural scenes. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-6, No. 6. Rankin, D., Salvaggio, C. Gallagher, T., & Schott, J.R. (1992). "Instrumentation and procedures for validation of synthetic infrared image generation (SIG) models." Proceedings SPIE, Infrared Technology XVIII, Vol. 1762, pp. 584-600. Ranson, K.J., Irons, J.R., & Williams, D.L. (1994). Multispectral bidirectional reflectance of northern forest canopies with the advanced solid-state array spectroradiometer (ASAS). Remote Sensing of Environment, Vol. 47, pp. 276-289. Salvaggio, C, Sirianni, J.D., & Schott, J.R. (1993). “Use of LOWTRAN-derived atmospheric parameters in synthetic image generation models.” Proceedings of the SPIE, Vol. 1938, No. 34, pp. 294-307. Schott, J.R., Raqueño, R., & Salvaggio, C. (1992). Incorporation of time-dependent thermodynamic model and a radiation propagation model into infrared three-dimensional synthetic image generation. Optical Engineering, Vol. 31, No. 7, pp. 1505-16. Schott, J.R., Salvaggio, C., Brown, S.D., & Rose, R. (1995). “Incorporation of texture in multispectral synethetic image generation models.” Presented at SPIE Target and Backgrounds: Characterization and Representation Conference, Orlando, FL. Sheffer, A.D., Jr., Cathcart, J.M., & Stewart, J.M. (1993). “Ocean background model for scene simulation.” Proceedings of the SPIE, Vol. 1938, No. 38, pp. 337-349. Stewart, S.R., Lyons, J.T., & Horvath, R. Simulated infrared imaging (SIRIM): “user’s tool for simulating target signatures (U).” Environmental Research Institute of Michigan.