Student Number 973202084 Author Candera Wijaya(洪若彬) Author's Email Address email@example.com Statistics This thesis had been viewed 536 times. Download 521 times. Department Civil Engineering Year 2009 Semester 2 Degree Master Type of Document Master's Thesis Language English Title Spatial Local Contrast Enhancement of Satellite Images Date of Defense 2010-06-17 Page Count 92 Keyword adjustable histogram equalization entropy segmentation Abstract The main purpose of image enhancement is to increase the contrast in order to bring out hidden details of an image. Therefore, the image enhancement generally is an important process to have a better image quality for visual applications. In the global approach, the enhancement methods generally use a single mapping function to enhance the whole image. However, a single enhancement mapping function can not improve image contrast satisfactorily since the contrast of an object is interfered by the whole image. Naturally, it is difficult to find a good mapping function to enhance the whole image. In this thesis, we proposed a new contrast enhancement technique which stretches the local contrast to improve the visibility of satellite images, while preserving its natural looks. The proposed method is based on segmentation of an input image that divided into small individual patches. Adjustable histogram equalization with dynamic threshold is applied for every single patch with the consideration of the gap problem appearing between patches. The threshold is based on an exponential function under the relationship between Shannon entropy index and adjustable histogram equalization weighting parameter. The larger entropy index on a segment, the smaller parameter value is used, and vice versa.
The results show that visibility improvement of specific objects is successfully enhanced using the proposed method. This thesis provided a new enhancement algorithm in enhancing contrast and characteristics of an image that could not be enhanced by global contrast enhancement or conventional method.
Table of Content Abstracti
List of Figuresvi
List of Tablesviii
Chapter 1 - Introduction1
Chapter 2 - Related works5
2.1Linear Histogram Stretching5
2.3Histogram Equalization (HE)7
2.4Local Histogram Equalization8
2.5Adjustable Histogram Equalization9
2.6Image Quality assessment10
2.6.1 Manual Assessment11
2.6.2 Quantification Assessment11
126.96.36.199 Shannon Entropy Index11
188.8.131.52 Michelson Contrast Index13
Chapter 3 - Methodology15
3.2Adjustable Histogram Equalization19
Chapter 4 - Study Area26
4.1 Quickbird Satellite Image27
4.2 IKONOS-2 Satellite Image28
4.3 Geo-Eye-1 Satellite Image29
4.4 FORMOSAT-2 Satellite Image30
4.5 SPOT-5 Satellite Image32
Chapter 5 - Experimental Results and Discussion34
5.1 Experimental Results of QuickBird satellite image35
5.2 Experimental Results of IKONOS-2 satellite image43
5.3 Experimental Results of GeoEye-1 satellite image51
5.4 Experimental Results of FORMOSAT-2 satellite image59
5.5 Experimental Results of SPOT-5 satellite image67
Chapter 6 - Conclusion77
Reference Adams, R. & Bischof, L., 1994. Seeded region growing, IEEE Transactions on Pattern Analysis and Machine Intelligence, 16 (6), pp. 641-647.
Arici, T., Dikbas, S. and Altunbasak, Y., 2009. A histogram modification framework and its application for image contrast enhancement, IEEE Transactions on image processing, 18 (9), pp. 1921-1935.
Gonzalez, R. C. and Woods, R. E., 1992. Digital image processing, Addison-Wesley Publishing Company, Inc.
Gonzalez, R. C. and Woods, R. E., 2001. Digital image processing (2nd ed.). New York: Prentice Hall.
Kim, D. H. and Cha, E. Y., 2009. Intensity surface stretching technique for contrast enhancement of digital photography, Multidim Syst Sign Process, 20, pp. 81–95.
Kim, J. Y., Kim, L. S. and Hwang, S. H., 2001. An advanced contrast enhancement using partially overlapped sub-block histogram equalization, IEEE Transactions on Circuits and Systems for Video Technology, 11 (4), pp. 475–484.
Kong, N. S. P. and Ibrahim, H., 2008. Color image enhancement using brightness preserving dynamic histogram equalization, IEEE Transactions on Consumer Electronics, 54 (4), pp. 1962-1968.
Peli, E., 1990. Contrast in complex images, Optical Society of America, 7 (11), pp. 2032-2040.
Shannon, E. C., 1948. A mathematical theory of communication. Bell SystemTechnical Journal, 27, pp. 379-423, 623-656.
Sheikh, H. R. and Bovik, A. C., 2006. Image information and visual quality. IEEE Transactions on Image Processing, 15(2), pp.430-444.
Stark, J. A., 2000. Adaptive image contrast enhancement using generalizations of histogram equalization. IEEE Transactions on Image Processing, 9(5), pp. 889-896.
Yoon, B. W. and Song, W. J., 2007 Image contrast enhancement based on the generalized histogram. Journal of Electronic Imaging, 16(3), pp. 033005-1-033005-8
Advisor Chi-Farn Chen(陳繼藩)
approve in 1 year
973202084.pdf Date of Submission 2010-07-22