Abstract

A regression-based model was developed relating aerial image quality, expressed in terms of the National Imagery Interpretability Rating Scale (NIIRS), to fundamental image attributes. The General Image-Quality Equation (GIQE) treats three main attributes: scale, expressed as the ground-sampled distance; sharpness, measured from the system modulation transfer function; and the signal-to-noise ratio. The GIQE can be applied to any visible sensor and predicts NIIRS ratings with a standard error of 0.3 NIIRS. The image attributes treated by the GIQE are influenced by system design and operation parameters. The GIQE allows system designers and operators to perform trade-offs for the optimization of image quality.

© 1997 Optical Society of America

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  1. L. A. Maver, C. D. Erdman, K. Riehl, “Imagery interpretability rating scales,” in Digest of Technical Papers: International Symposium of the Society for Information Display (Society for Information Display, Santa Ana, Calif., 1995), Vol. 26, pp. 117–120.
  2. IRARS Committee, General Image Quality Equation: Users Guide, Version 3.0, High Altitude Endurance Unmanned Aerial Vehicle Tier II+ distribution (IRARS Committee, Washington, D.C., 1994).
  3. J. C. Leachtenauer, “National Imagery Interpretability Rating Scales: overview and product description,” in ASPRS/ASCM Annual Convention and Exhibition Technical Papers: Remote Sensing and Photogrammetry (American Society for Photogrammetry and Remote Sensing and American Congress on Surveying and Mapping, Baltimore, Md., 1996), Vol. 1, pp. 262–272.
  4. H. L. Snyder, “Visual search and image quality,” (Aerospace Medical Research Laboratory, Wright-Patterson Air Force Base, Ohio, 1976).
  5. N. H. Nill, B. H. Bouzas, “Objective image quality measure derived from digital image power spectra,” Opt. Eng. 31, 813–825 (1992).
    [CrossRef]
  6. U.S. Department of the ArmyU.S. Department of the NavyU.S. Department of the Air Force, Photo Interpretation Handbook, TM30-45/NAVAER 10-35-610/AFM 200-50 (U.S. Government Printing Office, Washington, D.C., 1954).
  7. C. C. Bennett, S. H. Winterstein, J. D. Taylor, R. E. Kent, “A study of image quality and speeded intrinsic target recognition,” (IBM Federal Systems Division, Oswego, N.Y., 1963).
  8. Applied Psychology Corporation, “Performance of photographic interpreters as a function of time and image characteristics,” (Rome Air Development Center, Rome, N.Y., 1963).
  9. R. A. Erickson, J. C. Hemingway, “Image identification on television,” (Naval Weapons Center, China Lake, Calif., 1970).
  10. H. C. Borrough, R. F. Fallis, T. H. Warnock, J. H. Britt, “Quantitative determination of image quality,” (Boeing Aerospace Company, Kent, Wash., 1967).
  11. H. L. Task, “An evaluation and comparison of several measures of image quality for television displays,” (Aerospace Medical Research Laboratory, Wright-Patterson Air Force Base, Ohio, 1979).
  12. R. A. Schindler, “Optical power spectrum analysis of processed imagery,” (Aerospace Medical Research Laboratory, Wright-Patterson Air Force Base, Ohio, 1979).
  13. F. A. Rossell, R. H. Willson, “Recent psychophysical experiments and the display signal-to-noise ratio concept,” in Perception of Displayed Information, L. M. Biberman, ed. (Plenum, New York, 1973).
    [CrossRef]
  14. R. J. Beaton, R. W. Monty, H. L. Snyder, “An evaluation of system quality metrics for hard-copy and soft-copy displays of digital imagery,” in Applications of Digital Image Processing VI, A. G. Tescher, ed., Proc. SPIE432, 320–328 (1983).
  15. R. E. Simmons, D. W. Cheeseman, Physique (eoi) User’s Guide, Version 3.10 (Eastman Kodak, Rochester, N.Y., 1991).
  16. For example, log10X = log2X/3.32.
  17. J. C. Leachtenauer, N. L. Salvaggio, “NIIRS prediction, use of the Briggs target,” in ASPRS/ASCM Annual Convention and Exhibition Technical Papers: Remote Sensing and Photogrammetry, (American Society for Photogrammetry and Remote Sensing and American Congress on Surveying and Mapping, Baltimore, Md., 1996), Vol. 1, pp. 282–291.
  18. The term λ(f-number)/P is the ratio of the wavelength times the f-number to the pixel pitch. A ratio of greater than 1 denotes oversampling relative to the cutoff frequency.

1992 (1)

N. H. Nill, B. H. Bouzas, “Objective image quality measure derived from digital image power spectra,” Opt. Eng. 31, 813–825 (1992).
[CrossRef]

Beaton, R. J.

R. J. Beaton, R. W. Monty, H. L. Snyder, “An evaluation of system quality metrics for hard-copy and soft-copy displays of digital imagery,” in Applications of Digital Image Processing VI, A. G. Tescher, ed., Proc. SPIE432, 320–328 (1983).

Bennett, C. C.

C. C. Bennett, S. H. Winterstein, J. D. Taylor, R. E. Kent, “A study of image quality and speeded intrinsic target recognition,” (IBM Federal Systems Division, Oswego, N.Y., 1963).

Borrough, H. C.

H. C. Borrough, R. F. Fallis, T. H. Warnock, J. H. Britt, “Quantitative determination of image quality,” (Boeing Aerospace Company, Kent, Wash., 1967).

Bouzas, B. H.

N. H. Nill, B. H. Bouzas, “Objective image quality measure derived from digital image power spectra,” Opt. Eng. 31, 813–825 (1992).
[CrossRef]

Britt, J. H.

H. C. Borrough, R. F. Fallis, T. H. Warnock, J. H. Britt, “Quantitative determination of image quality,” (Boeing Aerospace Company, Kent, Wash., 1967).

Cheeseman, D. W.

R. E. Simmons, D. W. Cheeseman, Physique (eoi) User’s Guide, Version 3.10 (Eastman Kodak, Rochester, N.Y., 1991).

Erdman, C. D.

L. A. Maver, C. D. Erdman, K. Riehl, “Imagery interpretability rating scales,” in Digest of Technical Papers: International Symposium of the Society for Information Display (Society for Information Display, Santa Ana, Calif., 1995), Vol. 26, pp. 117–120.

Erickson, R. A.

R. A. Erickson, J. C. Hemingway, “Image identification on television,” (Naval Weapons Center, China Lake, Calif., 1970).

Fallis, R. F.

H. C. Borrough, R. F. Fallis, T. H. Warnock, J. H. Britt, “Quantitative determination of image quality,” (Boeing Aerospace Company, Kent, Wash., 1967).

Hemingway, J. C.

R. A. Erickson, J. C. Hemingway, “Image identification on television,” (Naval Weapons Center, China Lake, Calif., 1970).

Kent, R. E.

C. C. Bennett, S. H. Winterstein, J. D. Taylor, R. E. Kent, “A study of image quality and speeded intrinsic target recognition,” (IBM Federal Systems Division, Oswego, N.Y., 1963).

Leachtenauer, J. C.

J. C. Leachtenauer, “National Imagery Interpretability Rating Scales: overview and product description,” in ASPRS/ASCM Annual Convention and Exhibition Technical Papers: Remote Sensing and Photogrammetry (American Society for Photogrammetry and Remote Sensing and American Congress on Surveying and Mapping, Baltimore, Md., 1996), Vol. 1, pp. 262–272.

J. C. Leachtenauer, N. L. Salvaggio, “NIIRS prediction, use of the Briggs target,” in ASPRS/ASCM Annual Convention and Exhibition Technical Papers: Remote Sensing and Photogrammetry, (American Society for Photogrammetry and Remote Sensing and American Congress on Surveying and Mapping, Baltimore, Md., 1996), Vol. 1, pp. 282–291.

Maver, L. A.

L. A. Maver, C. D. Erdman, K. Riehl, “Imagery interpretability rating scales,” in Digest of Technical Papers: International Symposium of the Society for Information Display (Society for Information Display, Santa Ana, Calif., 1995), Vol. 26, pp. 117–120.

Monty, R. W.

R. J. Beaton, R. W. Monty, H. L. Snyder, “An evaluation of system quality metrics for hard-copy and soft-copy displays of digital imagery,” in Applications of Digital Image Processing VI, A. G. Tescher, ed., Proc. SPIE432, 320–328 (1983).

Nill, N. H.

N. H. Nill, B. H. Bouzas, “Objective image quality measure derived from digital image power spectra,” Opt. Eng. 31, 813–825 (1992).
[CrossRef]

Riehl, K.

L. A. Maver, C. D. Erdman, K. Riehl, “Imagery interpretability rating scales,” in Digest of Technical Papers: International Symposium of the Society for Information Display (Society for Information Display, Santa Ana, Calif., 1995), Vol. 26, pp. 117–120.

Rossell, F. A.

F. A. Rossell, R. H. Willson, “Recent psychophysical experiments and the display signal-to-noise ratio concept,” in Perception of Displayed Information, L. M. Biberman, ed. (Plenum, New York, 1973).
[CrossRef]

Salvaggio, N. L.

J. C. Leachtenauer, N. L. Salvaggio, “NIIRS prediction, use of the Briggs target,” in ASPRS/ASCM Annual Convention and Exhibition Technical Papers: Remote Sensing and Photogrammetry, (American Society for Photogrammetry and Remote Sensing and American Congress on Surveying and Mapping, Baltimore, Md., 1996), Vol. 1, pp. 282–291.

Schindler, R. A.

R. A. Schindler, “Optical power spectrum analysis of processed imagery,” (Aerospace Medical Research Laboratory, Wright-Patterson Air Force Base, Ohio, 1979).

Simmons, R. E.

R. E. Simmons, D. W. Cheeseman, Physique (eoi) User’s Guide, Version 3.10 (Eastman Kodak, Rochester, N.Y., 1991).

Snyder, H. L.

H. L. Snyder, “Visual search and image quality,” (Aerospace Medical Research Laboratory, Wright-Patterson Air Force Base, Ohio, 1976).

R. J. Beaton, R. W. Monty, H. L. Snyder, “An evaluation of system quality metrics for hard-copy and soft-copy displays of digital imagery,” in Applications of Digital Image Processing VI, A. G. Tescher, ed., Proc. SPIE432, 320–328 (1983).

Task, H. L.

H. L. Task, “An evaluation and comparison of several measures of image quality for television displays,” (Aerospace Medical Research Laboratory, Wright-Patterson Air Force Base, Ohio, 1979).

Taylor, J. D.

C. C. Bennett, S. H. Winterstein, J. D. Taylor, R. E. Kent, “A study of image quality and speeded intrinsic target recognition,” (IBM Federal Systems Division, Oswego, N.Y., 1963).

Warnock, T. H.

H. C. Borrough, R. F. Fallis, T. H. Warnock, J. H. Britt, “Quantitative determination of image quality,” (Boeing Aerospace Company, Kent, Wash., 1967).

Willson, R. H.

F. A. Rossell, R. H. Willson, “Recent psychophysical experiments and the display signal-to-noise ratio concept,” in Perception of Displayed Information, L. M. Biberman, ed. (Plenum, New York, 1973).
[CrossRef]

Winterstein, S. H.

C. C. Bennett, S. H. Winterstein, J. D. Taylor, R. E. Kent, “A study of image quality and speeded intrinsic target recognition,” (IBM Federal Systems Division, Oswego, N.Y., 1963).

Opt. Eng. (1)

N. H. Nill, B. H. Bouzas, “Objective image quality measure derived from digital image power spectra,” Opt. Eng. 31, 813–825 (1992).
[CrossRef]

Other (17)

U.S. Department of the ArmyU.S. Department of the NavyU.S. Department of the Air Force, Photo Interpretation Handbook, TM30-45/NAVAER 10-35-610/AFM 200-50 (U.S. Government Printing Office, Washington, D.C., 1954).

C. C. Bennett, S. H. Winterstein, J. D. Taylor, R. E. Kent, “A study of image quality and speeded intrinsic target recognition,” (IBM Federal Systems Division, Oswego, N.Y., 1963).

Applied Psychology Corporation, “Performance of photographic interpreters as a function of time and image characteristics,” (Rome Air Development Center, Rome, N.Y., 1963).

R. A. Erickson, J. C. Hemingway, “Image identification on television,” (Naval Weapons Center, China Lake, Calif., 1970).

H. C. Borrough, R. F. Fallis, T. H. Warnock, J. H. Britt, “Quantitative determination of image quality,” (Boeing Aerospace Company, Kent, Wash., 1967).

H. L. Task, “An evaluation and comparison of several measures of image quality for television displays,” (Aerospace Medical Research Laboratory, Wright-Patterson Air Force Base, Ohio, 1979).

R. A. Schindler, “Optical power spectrum analysis of processed imagery,” (Aerospace Medical Research Laboratory, Wright-Patterson Air Force Base, Ohio, 1979).

F. A. Rossell, R. H. Willson, “Recent psychophysical experiments and the display signal-to-noise ratio concept,” in Perception of Displayed Information, L. M. Biberman, ed. (Plenum, New York, 1973).
[CrossRef]

R. J. Beaton, R. W. Monty, H. L. Snyder, “An evaluation of system quality metrics for hard-copy and soft-copy displays of digital imagery,” in Applications of Digital Image Processing VI, A. G. Tescher, ed., Proc. SPIE432, 320–328 (1983).

R. E. Simmons, D. W. Cheeseman, Physique (eoi) User’s Guide, Version 3.10 (Eastman Kodak, Rochester, N.Y., 1991).

For example, log10X = log2X/3.32.

J. C. Leachtenauer, N. L. Salvaggio, “NIIRS prediction, use of the Briggs target,” in ASPRS/ASCM Annual Convention and Exhibition Technical Papers: Remote Sensing and Photogrammetry, (American Society for Photogrammetry and Remote Sensing and American Congress on Surveying and Mapping, Baltimore, Md., 1996), Vol. 1, pp. 282–291.

The term λ(f-number)/P is the ratio of the wavelength times the f-number to the pixel pitch. A ratio of greater than 1 denotes oversampling relative to the cutoff frequency.

L. A. Maver, C. D. Erdman, K. Riehl, “Imagery interpretability rating scales,” in Digest of Technical Papers: International Symposium of the Society for Information Display (Society for Information Display, Santa Ana, Calif., 1995), Vol. 26, pp. 117–120.

IRARS Committee, General Image Quality Equation: Users Guide, Version 3.0, High Altitude Endurance Unmanned Aerial Vehicle Tier II+ distribution (IRARS Committee, Washington, D.C., 1994).

J. C. Leachtenauer, “National Imagery Interpretability Rating Scales: overview and product description,” in ASPRS/ASCM Annual Convention and Exhibition Technical Papers: Remote Sensing and Photogrammetry (American Society for Photogrammetry and Remote Sensing and American Congress on Surveying and Mapping, Baltimore, Md., 1996), Vol. 1, pp. 262–272.

H. L. Snyder, “Visual search and image quality,” (Aerospace Medical Research Laboratory, Wright-Patterson Air Force Base, Ohio, 1976).

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Figures (11)

Fig. 1
Fig. 1

Model of the GIQE.

Fig. 2
Fig. 2

RER measurement.

Fig. 3
Fig. 3

Computation of the overshoot H.

Fig. 4
Fig. 4

NIIRS values: observed versus predicted.

Fig. 5
Fig. 5

Residual plot for the GSD.

Fig. 6
Fig. 6

NIIRS values for the original GIQE: observed versus predicted.

Fig. 7
Fig. 7

Residual plot of the G/SNR for the original GIQE.

Fig. 8
Fig. 8

Predicted NIIRS values versus the GSD.

Fig. 9
Fig. 9

Predicted NIIRS values versus the RER.

Fig. 10
Fig. 10

Predicted NIIRS values versus the overshoot H.

Fig. 11
Fig. 11

Predicted NIIRS values versus the G/SNR.

Tables (3)

Tables Icon

Table 1 Visible NIIRS Operations by Level—March 1994a

Tables Icon

Table 2 Comparison of NIIRS Development and Test Sets

Tables Icon

Table 3 Range of Values in the Overall NIIRS Data Set

Equations (7)

Equations on this page are rendered with MathJax. Learn more.

NIIRS=11.81+3.32*log10RERGM/GSDGM-1.48*HGM-G/SNR,
GSD=pixel pitchfocal length*slant rangecoslook angle.
GSDGM=GSDX*GSDY*sin α1/2.
G=i=1Mj=1Nkernelij21/2.
SNR=S1-S2/N.
NIIRS=10.251-a log10 GSDGM+b log10 RERGM-0.656*H-0.344*G/SNR,
R2=1-Sy*x2/Sy2,

Metrics