Edge Segmentation of Satellite Image using Phase Congruency Model
In this paper, we present a method for edge
segmentation of satellite images based on 2-D Phase Congruency
(PC) model. The proposed approach is composed by two steps: The
contextual non linear smoothing algorithm (CNLS) is used to smooth
the input images. Then, the 2D stretched Gabor filter (S-G filter)
based on proposed angular variation is developed in order to avoid
the multiple responses in the previous work. An assessment of our
proposed method performance is provided in terms of accuracy of
satellite image edge segmentation. The proposed method is compared
with others known approaches.
[1] A. V. Oppenheim and J. S. Lim, "The importance of phase in signals",
Proceedings of the IEEE, vol.69, pp. 529-541, 1981.
[2] M. C. Morrone and D. C. Burr. "Feature detection in human vision: A
phase-dependent energy model". Proc. R. Soc. Lond. B, vol.235, pp.
221-245, 1988.
[3] S. Venkatesh and R. A. Owens. "An energy feature detection scheme".
In the International Conference on Image Processing, p. 553-557,
Singapore, 1989.
[4] S. Venkatesh and R. A. Owens. "On the classification of images
features". Pattern Recognition letters, Vol. 11, pp. 339-349, 1991.
[5] P. D Kovesi. "Image features from phase congruency". Videre: Journal
of Computer Vision Research, vol. 1, pp. 1-26, 1999
[6] P. D. Kovesi. "Invariant Measures of Image Features from Phase
Information". PhD thesis, The University of Western Australia, May
1996.
[7] P. D Kovesi, "Phase congruency detects corners and edges", The
Australian Pattern Recognition Society Conference: Sydney. p. 309-318,
December 2003.
[8] B Robbins and R Owens. "2D feature detection via local energy". Image
and Vision Computing, vol.15, pp 353-368, October 1997
[9] M. J. Robins. "Local energy features tracing in digital images and
volumes". PhD thesis, The University of Western Australia, June 1999
[10] C. Ronse. "The phase congruence model for edge detection in twodimensional
pictures: A mathematical study". PhD thesis, University
Louis Pastern, September 1995.
[11] C. Ronse. "The phase congruence model for edge detection in multidimensional
pictures". Technical report, Département d-Informatique,
Université Louis Pasteur, France. October 1997.
[12] Yuchi Huang, Stephen Lin, Stan Z. Li, Hanqing Lu, Heung-Yeung
Shum, "Face Alignment under Variable Illumination". IEEE
International Conference on Automatic Face and Gesture Recognition,
pp. 1-6, 2004
[13] Junzhou Huang and al. "Noise removal and impainting model for iris
image". International Conference on Image processing, pp.869-872,
ICIP 2004.
[14] M. J. Kyan, L. Guan, M. R. Arnison, and C. J. Cogswell. "Feature
Extraction of Chromosomes from 3-D Confocal Microscope Images".
IEEE Transactions on biomedical engineering, vol. 48, pp.1306-1318,
November 2001
[15] Guitao Cao, Pengfei Shi and Bing Hu. "Ultrasonic Liver
Characterization Using Phase Congruency". Proceedings of the 2005
IEEE Engineering in Medicine and Biology 27th Annual Conference
Shanghai, China, pp.1-4, September 2005
[16] Woei Chan, George Coghill, "Text analysis using local energy", Pattern
Recognition, Vol. 34, pp. 2523-2532, 2001.
[17] A.K. Jain, F. Farrokhnia, "Unsupervised texture segmentation using
Gabor filters", Pattern Recognition, Vol.24, pp. 1167-1186, 1991.
[18] T.S. Lee. "Image representation using 2D Gabor wavelets". IEEE Trans.
PAMI, 18(10), 959-971, 1996.
[19] D. Boukerroui, J.A. Noble and M. Brady. "On the Choice of Band-Pass
Quadrature Filters". Technical Report, MVL, Oxford University, 1999.
http://www.robots.ox.ac.uk/_djamal/.
[20] F. Heitger, R. Rosenthaler, R. Von Der Heydt, E. Peterhans, and O.
Kubler. "Simulation of neural mechanism: from simple to end-stopped
cells". Vision research, vol.32, pp. 963-981, 1992.
[21] X. Liu, D. L. Wang and J. R. Ramirez: "Boundary detection by
contextual non-linear smoothing". Pattern Recognition, Vol.33, pp. 263-
280, 2000
[22] M. Nagao and T. Matsuyama. "Edge preserving smoothing", Computer
Vision Graphics and Image Processing, vol. 9, pp 394-407, 1979.
[23] G.R. Arce, M.P. McLaughlin, "Theoretical analysis of the max/median
filter", IEEE Transactions on Acoustics, Speech, and Signal Processing,
pp. 60-69, 1987.
[24] J. Portilla, V. Strela, M. J. Wainwright and E. P. Simoncelli, "Image
Denoising using Scale Mixtures of Gaussians in the Wavelet Domain".
IEEE Transactions on Image Processing, vol. 12, pp. 1338-1351, 2003
[25] P. Kovesi, "Phase Preserving Denoising of Image". The Australian
Pattern Recognition Society Conference: DICTA'99, pp. 212-217.
December 1999
[26] S. G. Chang, B. Yu, and M. Vetterli, "Adaptive Wavelet Thresholding
for Image Denoising and Compression", IEEE transactions on image
processing, vol. 9, pp. 1532-1546, 2000
[27] D.L. Donoho. "Denoising by soft thresholding", IEEE Transactions on
Info. Theory, pp. 933-936, 1993.
[1] A. V. Oppenheim and J. S. Lim, "The importance of phase in signals",
Proceedings of the IEEE, vol.69, pp. 529-541, 1981.
[2] M. C. Morrone and D. C. Burr. "Feature detection in human vision: A
phase-dependent energy model". Proc. R. Soc. Lond. B, vol.235, pp.
221-245, 1988.
[3] S. Venkatesh and R. A. Owens. "An energy feature detection scheme".
In the International Conference on Image Processing, p. 553-557,
Singapore, 1989.
[4] S. Venkatesh and R. A. Owens. "On the classification of images
features". Pattern Recognition letters, Vol. 11, pp. 339-349, 1991.
[5] P. D Kovesi. "Image features from phase congruency". Videre: Journal
of Computer Vision Research, vol. 1, pp. 1-26, 1999
[6] P. D. Kovesi. "Invariant Measures of Image Features from Phase
Information". PhD thesis, The University of Western Australia, May
1996.
[7] P. D Kovesi, "Phase congruency detects corners and edges", The
Australian Pattern Recognition Society Conference: Sydney. p. 309-318,
December 2003.
[8] B Robbins and R Owens. "2D feature detection via local energy". Image
and Vision Computing, vol.15, pp 353-368, October 1997
[9] M. J. Robins. "Local energy features tracing in digital images and
volumes". PhD thesis, The University of Western Australia, June 1999
[10] C. Ronse. "The phase congruence model for edge detection in twodimensional
pictures: A mathematical study". PhD thesis, University
Louis Pastern, September 1995.
[11] C. Ronse. "The phase congruence model for edge detection in multidimensional
pictures". Technical report, Département d-Informatique,
Université Louis Pasteur, France. October 1997.
[12] Yuchi Huang, Stephen Lin, Stan Z. Li, Hanqing Lu, Heung-Yeung
Shum, "Face Alignment under Variable Illumination". IEEE
International Conference on Automatic Face and Gesture Recognition,
pp. 1-6, 2004
[13] Junzhou Huang and al. "Noise removal and impainting model for iris
image". International Conference on Image processing, pp.869-872,
ICIP 2004.
[14] M. J. Kyan, L. Guan, M. R. Arnison, and C. J. Cogswell. "Feature
Extraction of Chromosomes from 3-D Confocal Microscope Images".
IEEE Transactions on biomedical engineering, vol. 48, pp.1306-1318,
November 2001
[15] Guitao Cao, Pengfei Shi and Bing Hu. "Ultrasonic Liver
Characterization Using Phase Congruency". Proceedings of the 2005
IEEE Engineering in Medicine and Biology 27th Annual Conference
Shanghai, China, pp.1-4, September 2005
[16] Woei Chan, George Coghill, "Text analysis using local energy", Pattern
Recognition, Vol. 34, pp. 2523-2532, 2001.
[17] A.K. Jain, F. Farrokhnia, "Unsupervised texture segmentation using
Gabor filters", Pattern Recognition, Vol.24, pp. 1167-1186, 1991.
[18] T.S. Lee. "Image representation using 2D Gabor wavelets". IEEE Trans.
PAMI, 18(10), 959-971, 1996.
[19] D. Boukerroui, J.A. Noble and M. Brady. "On the Choice of Band-Pass
Quadrature Filters". Technical Report, MVL, Oxford University, 1999.
http://www.robots.ox.ac.uk/_djamal/.
[20] F. Heitger, R. Rosenthaler, R. Von Der Heydt, E. Peterhans, and O.
Kubler. "Simulation of neural mechanism: from simple to end-stopped
cells". Vision research, vol.32, pp. 963-981, 1992.
[21] X. Liu, D. L. Wang and J. R. Ramirez: "Boundary detection by
contextual non-linear smoothing". Pattern Recognition, Vol.33, pp. 263-
280, 2000
[22] M. Nagao and T. Matsuyama. "Edge preserving smoothing", Computer
Vision Graphics and Image Processing, vol. 9, pp 394-407, 1979.
[23] G.R. Arce, M.P. McLaughlin, "Theoretical analysis of the max/median
filter", IEEE Transactions on Acoustics, Speech, and Signal Processing,
pp. 60-69, 1987.
[24] J. Portilla, V. Strela, M. J. Wainwright and E. P. Simoncelli, "Image
Denoising using Scale Mixtures of Gaussians in the Wavelet Domain".
IEEE Transactions on Image Processing, vol. 12, pp. 1338-1351, 2003
[25] P. Kovesi, "Phase Preserving Denoising of Image". The Australian
Pattern Recognition Society Conference: DICTA'99, pp. 212-217.
December 1999
[26] S. G. Chang, B. Yu, and M. Vetterli, "Adaptive Wavelet Thresholding
for Image Denoising and Compression", IEEE transactions on image
processing, vol. 9, pp. 1532-1546, 2000
[27] D.L. Donoho. "Denoising by soft thresholding", IEEE Transactions on
Info. Theory, pp. 933-936, 1993.
@article{"International Journal of Electrical, Electronic and Communication Sciences:50277", author = "Ahmed Zaafouri and Mounir Sayadi and Farhat Fnaiech", title = "Edge Segmentation of Satellite Image using Phase Congruency Model", abstract = "In this paper, we present a method for edge
segmentation of satellite images based on 2-D Phase Congruency
(PC) model. The proposed approach is composed by two steps: The
contextual non linear smoothing algorithm (CNLS) is used to smooth
the input images. Then, the 2D stretched Gabor filter (S-G filter)
based on proposed angular variation is developed in order to avoid
the multiple responses in the previous work. An assessment of our
proposed method performance is provided in terms of accuracy of
satellite image edge segmentation. The proposed method is compared
with others known approaches.", keywords = "Edge segmentation, Phase congruency model,Satellite images, Stretched Gabor filter", volume = "4", number = "1", pages = "1-6", }
