Abstract

Imaging systems comparisons remains today a sensitive subject because of the difficulty to merge radiometric and spatial dimensions into a single, easy to use, parameter. By leaning explicitly on professional image users and their requirements we show how to build such a criterion, called Mission-Quality. A specific observation campaign is described and its results are used to calibrate and carry first proof of the criterion adequacy.

©2008 Optical Society of America

Full Article  |  PDF Article
OSA Recommended Articles
Mission-driven evaluation of imaging system quality

Alain Philippe Kattnig, Ouamar Ferhani, and Jérôme Primot
J. Opt. Soc. Am. A 18(12) 3007-3017 (2001)

Imaging system design for improved information capacity

Carl L. Fales, Friedrich O. Huck, and Richard W. Samms
Appl. Opt. 23(6) 872-888 (1984)

Augmented performance criterion for thermal imaging systems

J. G. Vortman and A. Bar-Lev
J. Opt. Soc. Am. A 3(5) 750-754 (1986)

More Recommended Articles

References

  • View by:
  • Article Order
  • |
  • Year
  • |
  • Author
  • |
  • Publication
  1. A. P. Kattnig, O. Ferhani, and J. Primot, “Mission-driven evaluation of imaging system quality,” J. Opt. Soc. Am. A 18, 3007–3017 (2001).
    [Crossref]
  2. A. P. Kattnig, O. Ferhani, and J. Primot, “A telescope design and performance analysis tool: the mission-quality criterion,” Proc. SPIE 5497, 396–404 (2004).
    [Crossref]
  3. A. Torralba and P. Sinha, “Statistical context priming for object detection,” Eighth International Conference on Computer Vision (ICCV’01), 763–770 (2001).
  4. C. L. Fales, F. O. Huck, and R. W. Samms, “Imaging system design for improved information capacity,” Appl. Opt. 23, 872–888 (1984).
    [Crossref] [PubMed]
  5. STANAG 3769 (about the minimal resolution needed for photographic interpretation), NATO Standardization Agreements (NATO, Brussels).
  6. A. van Meeteren, “Characterization of task performance with viewing instruments,” J. Opt. Soc. Am. A 7, 2016–2023 (1990).
    [Crossref] [PubMed]
  7. D. Sheffer and D. Ingman, “The informational difference concept in analyzing target recognition issues,” J. Opt. Soc. Am. A 14, 1431–1438 (1997).
    [Crossref]
  8. A. H. Lettington, D. Dunn, A. M. Fairhurst, and Y. Fang, “Proposed performance measures for imaging systems with discrete detector arrays,” J. Mod. Opt. 48, 115–123 (2001).
  9. Imagery Resolution Assessments and Reporting (IRARS) Committee, “National Imagery Interpretability Rating Scale (NIIRS)”, http://www.fas.org/irp/imint/niirs_c/guide.htm.
  10. J. C. Leachtenauer, W. Malila, J. Irvine, L. Colburn, and N. Salvaggio, “General image-quality equation: GIQE,” Appl. Opt. 36, 8322–8328 (1997).
    [Crossref]
  11. www.ermapper.com

2004 (1)

A. P. Kattnig, O. Ferhani, and J. Primot, “A telescope design and performance analysis tool: the mission-quality criterion,” Proc. SPIE 5497, 396–404 (2004).
[Crossref]

2001 (2)

A. P. Kattnig, O. Ferhani, and J. Primot, “Mission-driven evaluation of imaging system quality,” J. Opt. Soc. Am. A 18, 3007–3017 (2001).
[Crossref]

A. H. Lettington, D. Dunn, A. M. Fairhurst, and Y. Fang, “Proposed performance measures for imaging systems with discrete detector arrays,” J. Mod. Opt. 48, 115–123 (2001).

1997 (2)

1990 (1)

1984 (1)

Colburn, L.

Dunn, D.

A. H. Lettington, D. Dunn, A. M. Fairhurst, and Y. Fang, “Proposed performance measures for imaging systems with discrete detector arrays,” J. Mod. Opt. 48, 115–123 (2001).

Fairhurst, A. M.

A. H. Lettington, D. Dunn, A. M. Fairhurst, and Y. Fang, “Proposed performance measures for imaging systems with discrete detector arrays,” J. Mod. Opt. 48, 115–123 (2001).

Fales, C. L.

Fang, Y.

A. H. Lettington, D. Dunn, A. M. Fairhurst, and Y. Fang, “Proposed performance measures for imaging systems with discrete detector arrays,” J. Mod. Opt. 48, 115–123 (2001).

Ferhani, O.

A. P. Kattnig, O. Ferhani, and J. Primot, “A telescope design and performance analysis tool: the mission-quality criterion,” Proc. SPIE 5497, 396–404 (2004).
[Crossref]

A. P. Kattnig, O. Ferhani, and J. Primot, “Mission-driven evaluation of imaging system quality,” J. Opt. Soc. Am. A 18, 3007–3017 (2001).
[Crossref]

Huck, F. O.

Ingman, D.

Irvine, J.

Kattnig, A. P.

A. P. Kattnig, O. Ferhani, and J. Primot, “A telescope design and performance analysis tool: the mission-quality criterion,” Proc. SPIE 5497, 396–404 (2004).
[Crossref]

A. P. Kattnig, O. Ferhani, and J. Primot, “Mission-driven evaluation of imaging system quality,” J. Opt. Soc. Am. A 18, 3007–3017 (2001).
[Crossref]

Leachtenauer, J. C.

Lettington, A. H.

A. H. Lettington, D. Dunn, A. M. Fairhurst, and Y. Fang, “Proposed performance measures for imaging systems with discrete detector arrays,” J. Mod. Opt. 48, 115–123 (2001).

Malila, W.

Primot, J.

A. P. Kattnig, O. Ferhani, and J. Primot, “A telescope design and performance analysis tool: the mission-quality criterion,” Proc. SPIE 5497, 396–404 (2004).
[Crossref]

A. P. Kattnig, O. Ferhani, and J. Primot, “Mission-driven evaluation of imaging system quality,” J. Opt. Soc. Am. A 18, 3007–3017 (2001).
[Crossref]

Salvaggio, N.

Samms, R. W.

Sheffer, D.

Sinha, P.

A. Torralba and P. Sinha, “Statistical context priming for object detection,” Eighth International Conference on Computer Vision (ICCV’01), 763–770 (2001).

Torralba, A.

A. Torralba and P. Sinha, “Statistical context priming for object detection,” Eighth International Conference on Computer Vision (ICCV’01), 763–770 (2001).

van Meeteren, A.

Appl. Opt. (2)

J. Mod. Opt. (1)

A. H. Lettington, D. Dunn, A. M. Fairhurst, and Y. Fang, “Proposed performance measures for imaging systems with discrete detector arrays,” J. Mod. Opt. 48, 115–123 (2001).

J. Opt. Soc. Am. A (3)

Proc. SPIE (1)

A. P. Kattnig, O. Ferhani, and J. Primot, “A telescope design and performance analysis tool: the mission-quality criterion,” Proc. SPIE 5497, 396–404 (2004).
[Crossref]

Other (4)

A. Torralba and P. Sinha, “Statistical context priming for object detection,” Eighth International Conference on Computer Vision (ICCV’01), 763–770 (2001).

STANAG 3769 (about the minimal resolution needed for photographic interpretation), NATO Standardization Agreements (NATO, Brussels).

Imagery Resolution Assessments and Reporting (IRARS) Committee, “National Imagery Interpretability Rating Scale (NIIRS)”, http://www.fas.org/irp/imint/niirs_c/guide.htm.

www.ermapper.com

Cited By

OSA participates in Crossref's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (6)

Fig. 1.
Fig. 1. Model of image acquisition and reconstruction. III(x,y) being the two-dimensional Dirac comb and h(x,y) the point-spread function of the imaging system.

Download Full Size | PPT Slide | PDF

Fig. 2.
Fig. 2. Correlation between photo-interpreters average ratings and Mission-Quality predictions against different constant values defining the noise component of the Mission-Quality criterion.

Download Full Size | PPT Slide | PDF

Fig. 3.
Fig. 3. Averaged photo-interpreters ratings of presented images versus its modified Mission-Quality predictions. A red line is drawn, linking the two unambiguous extreme points of the plot.

Download Full Size | PPT Slide | PDF

Fig. 4.
Fig. 4. (a). Averaged photo-interpreters ratings of presented images versus its modified Mission-Quality value with a Noise power of 0 digitization levels. (b). Noise power of 50 digitization levels. (c). Noise power of 100 digitization levels. (d). Noise power of 150 digitization levels.

Download Full Size | PPT Slide | PDF

Fig. 5.
Fig. 5. (a). Averaged photo-interpreters ratings of presented images versus its modified Mission-Quality value with a f-number of 5. (b) f-number of 10. (c) f-number of 15. (d) f-number of 20.

Download Full Size | PPT Slide | PDF

Fig. 6.
Fig. 6. (a). Averaged photo-interpreters ratings of presented images versus its modified Mission-Quality value with a detector size of 10 microns. (b) Detector size of 20 microns. (c) Detector size of 30 microns.

Download Full Size | PPT Slide | PDF

Tables (2)

Tables Icon

Table 1. Rating scale used to evaluate the quality of images toward the observation mission

View Table | View all tables in this article
Tables Icon

Table 2. Values of imaging systems parameters

View Table | View all tables in this article

Equations (29)

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

S ( i , j ) = G × [ L ( x , y ) * h ( x , y ) ] ( i × l s , j × l s ) + N ( i , j )
L R ( x , y ) = K × { [ L ( x , y ) * h ( x , y ) + N BL ( x , y ) × III ( x l s , y l s ) ] } * [ sinc ( x l s ) × sinc ( y l s ) ]
Fidelity 2 = ∥ Object − Image ∥ L 2 2 ∥ Object ∥ L 2 2 = ∬ ] − ∞ , + ∞ [ 2 ∣ Object ( x , y ) − Image ( x , y ) ∣ 2 dxdy ∬ ] − ∞ , + ∞ [ 2 ∣ Object ( x , y ) ∣ 2 dxdy
Quality Mission 2 = ∥ Object ∣ D − Image ∣ D ∥ L 2 2 ∥ Object ∣ D ∥ L 2 2 = ∬ D ∣ Object ( x , y ) − Image ( x , y ) ∣ 2 dxdy ∬ D ∣ Object ( x , y ) ∣ 2 dxdy
Quality Mission 2 = ∬ ] − ∞ , + − ∞ [ 2 ∣ Object ̂ ( v x , v y ) − Image ̂ ∣ D ( v x , v y ) ∣ 2 d v x d v y ∬ ] − − ∞ , + − ∞ [ 2 ∣ Object ̂ ( v x , v y ) ∣ 2 d v x d v y
Quality Mission 2 = ∬ ] − v max , + v max [ 2 ∣ Object ̂ ( v x , v y ) − Image ̂ ∣ D ( v x , v y ) ∣ 2 d v x d v y ∬ ] − v max , + v max [ 2 ∣ Object ̂ ( v x , v y ) ∣ 2 d v x d v y
Quality Mission 2 = Quality Mission Filtering 2 + Quality Mission Noise 2 + Quality Mission Loss 2 + Quality Mission Aliasing 2
Quality Mission Filtering 2 = ∬ ] − v e 2 , v e 2 [ 2 ∣ ( Object ̂ − h ̂ × Object ̂ ) ( v x , v y ) ∣ 2 d v x d v y ∬ ] − v max , v max [ 2 ∣ Object ̂ ( v x , v y ) ∣ 2 d v x d v y
Quality Mission Aliasing 2 = 1 ∬ ] − ν max , ν max [ 2 ∣ Object ̂ ( ν x , ν y ) ∣ 2 d ν x d ν y × [ ∬ ] − ν e 2 , ν e 2 [ 2 ∣ ∑ ( i , j ) ≠ ( 0 , 0 ) ( h ̂ × Object ̂ ) ( ν x − i ν e , ν y − j ν e ) ∣ 2 d ν x d ν y …
− 2 × ∬ ] − ν e 2 , ν e 2 [ 2 ∑ ( i , j ) ≠ ( 0 , 0 ) ( h ̂ × Object ̂ ) ( ν x − i ν e , ν y − j ν e ) × [ ( 1 − h ̂ ) × Object ̂ ] ( ν x , ν y ) d ν x d ν y ]
Quality Mission Noise 2 = ∬ ] − v e 2 , v e 2 [ 2 ∣ Noise ̂ ∣ D ( v x , v y ) ∣ 2 d v x d v y ∬ ] − v max , v max [ 2 ∣ Object ̂ ( v x , v y ) ∣ 2 d v x d v y
Quality Mission Loss 2 = ∬ ] − v max , v max [ 2 − ] v e 2 , v e 2 [ 2 ∣ Object ̂ ( v x , v y ) ∣ 2 d v x d v y ∬ ] − v max , v max [ 2 ∣ Object ̂ ( v x , v y ) ∣ 2 d v x d v y
if ( i , j ) ≠ ( 0 , 0 ) then E [ ( h ̂ × Object ̂ ) ( v x − i v e , v y − j v e ) × [ ( 1 − h ̂ ) × Object ̂ ] ( v x , v y ) ] = 0 , thus
∬ ] − v e 2 , v e 2 [ 2 ∑ ( i , j ) ≠ ( 0 , 0 ) ( h ̂ × Object ̂ ) ( v x − i v e , v y − j v e ) × [ ( 1 − h ̂ ) × Object ̂ ] ( v x , v y ) d v x d v y = 0
∬ ] − v e 2 , v e 2 [ 2 ∣ ∑ ( i , j ) ≠ ( 0 , 0 ) ( h ̂ × Object ̂ ) ( v x − i v e , v y − j v e ) ∣ 2 d v x d v y = ∬ ] − ∞ , ∞ [ 2 − ] − v e 2 , v e 2 [ 2 ∣ ( h ̂ × Object ̂ ) ( v x , v y ) ∣ 2
Quality Mission Aliasing 2 = ∬ ] − ∞ , ∞ [ 2 − ] − v e 2 , v e 2 [ 2 ∣ ( h ̂ × Object ̂ ) ( v x , v y ) ∣ 2 d v x d v y ∬ ] − v max , v max [ 2 ∣ Object ̂ ( v x , v y ) ∣ 2 d v x d v y
v max = 2 MROS standard
Quality Mission Noise 2 = K × ∬ ] v e 2 , v e 2 [ 2 ∣ Noise ̂ ∣ Disk ( v x , v y ) ∣ 2 d v x d v y ∬ ] − v max , v max [ 2 ∣ Disk ̂ ( v x , v y ) ∣ 2 d v x d v y
Disk ̂ ( v x , v y ) = 2 × J 1 ( 2 π × MROS 2 × v x 2 + v y 2 ) 2 π × MROS 2 × v x 2 + v y 2 = 2 × J 1 ( 2 π × v x 2 + v y 2 v max ) 2 π × v x 2 + v y 2 v max
∬ ] − v max , v max [ 2 ∣ Disk ̂ ( v x , v y ) ∣ 2 d v x d v y ≈ 0.959 × ∬ ] − ∞ , ∞ [ 2 ∣ Disk ̂ ( v x , v y ) ∣ 2 d v x d v y
Q u a l i t y M i s s i o n N o i s e 2 = K ′ × σ N o i s e 2 × S u r f a c e D i s k 0.959 × C o n t r a s t 2 × S u r f a c e D i s k
                                            = ( K × σ N o i s e C o n t r a s t ) 2
Photo − Interpreters Rating = 6 × [ 1 − Quality Mission ]
Contrast σ Noise = 6 0.5 ≈ 5
Quality Mission Noise = 6 × σ Noise Contrast
Quality Mission Filtering 2 = ∬ ] − ν e 2 , ν e 2 [ 2 ∣ ( Object ̂ − h ̂ × Object ̂ ) ( ν x , ν y ) ∣ 2 d ν x d ν y ∬ ] − ν max , ν max [ 2 ∣ Object ̂ ( ν x , ν y ) ∣ 2 d ν x d ν y
Quality Mission Aliasing 2 = ∬ ] − ∞ , ∞ [ 2 − ] − ν e 2 , ν e 2 [ 2 ∣ ( h ̂ × Object ̂ ) ( ν x , ν y ) ∣ 2 d ν x , d v y ∬ ] − ν max , ν max [ 2 ∣ Object ̂ ( ν x , ν y ) ∣ 2 d ν x d ν y
Quality Mission Noise = 6 × σ Noise Contrast
Q u a l i t y M i s s i o n L o s s 2 = ] − v max , v max [ 2 ∬ − ] − v e 2 , v e 2 [ 2 ∣ Object ̂ ( v x , v y ) ∣ 2 dv x d v y ∬ ] − v max , v max [ 2 ∣ Object ̂ ( v x , v y ) ∣ 2 d v x d v y

Metrics