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Student Number 973202084
Author Candera Wijaya(洪若彬)
Author's Email Address 973202084@cc.ncu.edu.tw
Statistics This thesis had been viewed 548 times. Download 534 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
    摘要ii
    Acknowledgementsiii
    Contentsiv
    List of Figuresvi
    List of Tablesviii
    Chapter 1 - Introduction1
    1.1Preview1
    1.2Motivation2
    1.3Thesis Organization4
    Chapter 2 - Related works5
    2.1Linear Histogram Stretching5
    2.2Gamma Transform6
    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
    2.6.2.1 Shannon Entropy Index11
    2.6.2.2 Michelson Contrast Index13
    2.7Review14
    Chapter 3 - Methodology15
    3.1Segmentation16
    3.2Adjustable Histogram Equalization19
    3.3Smoothing23
    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
    References79
    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
    http://www.digitalglobe.com/
    http://www.wikipedia.org/
    張宏宇,2008,「模糊分類法應用於衛星影像之對比增揚」,碩士論文,國立中央大學土木工程研究所。
    Advisor
  • Chi-Farn Chen(陳繼藩)
  • Files
  • 973202084.pdf
  • approve in 1 year
    Date of Submission 2010-07-22

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