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Computación y Sistemas

Print version ISSN 1405-5546

Comp. y Sist. vol.8 n.4 México Apr./Jun. 2005

 

Artículos

 

Quantifying Contrast Methods through Morphological Gradient

 

Métodos para Cuantificar el Contraste a través del Gradiente Morfológico

 

Jorge D. Mendiola–Santibañez1, Iván R. Terol–Villalobos2

 

1 Universidad Autónoma de Querétaro
Doctorado en Ingeniería,
76000, Querétaro, México
mendijor@uaq.mx

2 CIDETEQ, S.C.,
Parque Tecnológico S/N, San Fandila–Pedro Escobedo, 76700,
Querétaro, México
famter@ciateq.net.mx

 

Article received on september 14, 2004; accepted on march 17, 2005

 

Abstract

In this work two quantifying contrast models are proposed. The first contrast measure method employs the concept denominated difference of contrast; while the second one takes in consideration the luminance gradient concept. These models allow the selection of the best parameters in a group of output images obtained from the application of the morphological toggle mappings with size criteria. These morphological transformations have the characteristic of modifying the output contrast based on some proximity criterion. In order to illustrate the performance of these quantifying contrast models, a number of images were processed and compared at pixel and partition level.

Keywords: Contrast Measure, Toggle Mappings, Flat Zone, Partition, Visualization.

 

Resumen

En este trabajo son propuestos dos modelos para cuantificar el contraste. El primer método para evaluar el contraste emplea el concepto denominado diferencia de contraste, mientras que el segundo método toma en consideración el concepto de gradiente de la luminancia. Estos modelos permiten la selección del mejor parámetro en un grupo de imagines de salida obtenidas a partir de la aplicación de los mapeos de contraste morfológicos con criterio de tamaño. Estas transformaciones morfológicas tienen la característica de modificar el contraste de salida basados algún criterio de proximidad. Para ilustrar el comportamiento de estos modelos que permiten cuantificar el contraste, un número de imágenes fueron procesadas y comparadas tanto a nivel píxel como a nivel partición.

Palabras Clave: Medida de Contraste, Mapeos de Contraste, Zona Plana, Partición, Visualización.

 

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Acknowledgments

The author Jorge D. Mendiola Santibañez would like to thank CONACyT México for the financial support. The author I. Terol would like to thank Diego Rodrigo and Darío T.G. for their great encouragement. This work was partially funded by the government agency CONACyT (Mexico) under the grant 41170.

 

References

1. Agaian, S.S., Panetta, K., and Grigoryan, A.M.: Transform–Based Image Enhancement Algorithms with Performance Measure, IEEE Transactions on Image Processing, 10(2001) 367–382.        [ Links ]

2. Ashdown, I.: Luminance gradients: photometric analysis and perceptual reproduction, Journal of the Illuminating Engineering Society, 25 (1996) 69–82.        [ Links ]

3. Barten, P. G. J.:Physical model for the contrast sensitivity of the turnan eye, in Proceedings of SPIE, 1666 (1992) 57–72.        [ Links ]

4. Beghdadi, A. and Negrate, A. L.: Contrast enhancement technique based on local detection of edges, Camput. Vis., Graph., Image Process., 46 (1989) 162–274.        [ Links ]

5. Blommaert, F. J. J. and Martens, J.: An object–oriented model for brightness perception, Spatial Vision, 1, (1990) 15–41.        [ Links ]

6. Gordon ,R., and Rangayyan, R.M.: Feature enhancement of film mammograms using fixed and adaptative neighbourhoods, Appl. Opt., 23, (1984) 560–564.        [ Links ]

7. Horn, B. K. P.: Determining lightness from an image, Computer Graphics and Image Processing, 3, (1977) 277–299.        [ Links ]

8. Jain, A. K., Fundamentals of Digital Image Processing. Englewood Cliffs, NJ: Prentice Hall (1989).        [ Links ]

9. Kirn, J. K., Park, J. M., Song, K. S., and Park, H.W.: Adaptive mammo–graphic image enhancement using first derivative and local statistics, IEEE Trans. Med. Imag., 16 (1997) 495–502.        [ Links ]

10. Maragos P. and Schafer R. W.: Morphological Filters–Part I: Their set–theoretic analysis and relations to linear shift–invariant filters, IEEE Trans. Acoust., Speech, SignaI Processing, 35 (1987) 1153–1169.        [ Links ]

11. Mendiola–Santibañez, J.D. and Terol–Villalobos, I. R.:Morphological contrast enhancement using connected transformations, in Proceedings of SPIE, 4667 (2002) 365–376.        [ Links ]

12. Mendiola–Santibañez, J.D and Terol–Villalobos, I. R., "Mapeos de Contraste Morfológicos sobre Particiones Basados en la Noción de Zona Plana" Computación y Sistemas, 6,(2002) 25–37.        [ Links ]

13. Meyer, F. and Serra, J., : Activity Mappings, Signal Processing,16, (1989) 303–317.        [ Links ]

14. Morrow, W. M., Paranjape, R. B., Rangayyan, R. M., and De–sautels, J. E. L: Region–based contrast enhancement of mammograms, IEEE Trans. Med. Imag., 11, (1992) 392–406.        [ Links ]

15. Peli, E.:Cantrast in Complex Irnages, J. Optical Society of America, 7, (1990) 2032–2040.        [ Links ]

16. Serra, J.: lmage Analysis and Mathematical Morphology, J. Serra, Ed., Vol. I, Academic Press, New York ( 1982).        [ Links ]

17. Serra, J.: Toggle Mappings, Technical report N–18/88/MM, Centre de Morphologie Mathematique, ENSMP, Fontainebleau, France (1988).        [ Links ]

18. Serra, J.: lmage Analysis and Mathematical Morphology, J. Serra, Ed., Vol. II, Academic, New York (1988).        [ Links ]

19. Serra, J.: Anamorphoses and function lattices, in Mathematical Morphology in lmage Processing, E. Dougerty, ed., Dekker, New York (1992).        [ Links ]

20. Serra, J.: Morphological filtering: An overview, Signal Processing, 38 (1993) 3–11.        [ Links ]

21. Stockham, T. G. Jr.: Image processing in the context of a visual model, Proc. IEEE, 60, (1972) 828–842.        [ Links ]

22. Terol–Villalobos, I. R: Nonincreasing filtres using morphological gradient criteria, Optical Engineering, 35 (1996) 3172–3182.        [ Links ]

23. Terol– Villalobos, I. R and Cruz–Mandujano, J.A.: Contrast enhancement and image segmentation using a class of morphological nonincreasing filters, Journal of Electronic lmaging, 7 (1998) 641–654.        [ Links ]

24. Terol–Villalobos, I. R: Toggle mappings and some related transformations: A study of contrast enhancement", in Mathernatical Morphology and lts Applications to Image and Signal Processing, H.J.A.M. Heijmans and J.B.T.M. Roerdink , Eds., Kluwer Acadernic Publishers, The Netherlands (1998) 11–18.        [ Links ]

25. Terol– Villalobos, I.R: Morphological Image Enhancement and Segmentation, in Advanccs in lmaging and Electron Physics, Editor Peter W. Hawkes, Vol. 118, Chapter 4, Academic Press (2001) 207–273.        [ Links ]

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