Title page for 90522041


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Student Number 90522041
Author Jia-Hau Guo(郭家豪)
Author's Email Address mayako.guo@msa.hinet.net
Statistics This thesis had been viewed 3329 times. Download 2496 times.
Department Computer Science and Information Engineering
Year 2002
Semester 2
Degree Master
Type of Document Master's Thesis
Language zh-TW.Big5 Chinese
Title The Study of Exposure Compensation for Backlight Images and Color Reduction
Date of Defense 2003-06-25
Page Count 68
Keyword
  • clustering
  • color quantization
  • histogram equalization
  • image enhancement
  • Abstract In recent years, color images occupy an extensive area of the information used in computer technology. Therefore, how to efficiently process color images becomes a demanding task. In this thesis, two algorithms for processing color images are proposed.
    Most of digital cameras have many appealing features, such as auto focus, auto exposure, etc, which enable user to easily take good pictures under various shot conditions, users still have chances of getting backlight images. This paper presents a new algorithm for compensating exposure in the case of backlighting, regardless of the position of objects. To achieve this compensation, the fuzzy C-means algorithm is first used to extract features from a backlight image. Then these extracted features are input into an SOM-based fuzzy system to determine the amount of compensation. A set of 26 images were tested to illustrate the performance of the algorithm.
    In the second part of the thesis, A region based color reduction algorithm is proposed. In this algorithm, a superposed 3D histogram is first calculated. Then the sorted histogram list will be fed into a region- growing-and-merging-algorithm to determine the number of quantized color for each region. By using the computed numbers, the K-means algorithm is employed to extract the palette colors. Several experimental and comparative results illustrate the performance of the proposed algorithm.
    Table of Content 圖目錄II
    表目錄III
    表目錄III
    第一章 序論1
    1.1 研究動機1
    1.2 論文架構2
    第二章 背光影像自動補償4
    2.1 研究動機4
    2.2 背光影像自動補償演算法8
    2.2.1 色彩空間9
    2.2.2 背光影像補償12
    2.2.3 以自我組織映射圖為基礎的類神經模糊系統16
    2.3 實驗結果23
    第三章 色彩減量29
    3.1 研究動機29
    3.2 文獻探討32
    3.3 區域為基礎的色彩減量演算法35
    3.3.1 區域增長36
    3.3.2 聚合演算法44
    3.3.3 分群與像素的對應47
    3.4 實驗結果51
    第四章 結論與展望61
    第五章 參考文獻63
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    Advisor
  • Mu-Chun Su(蘇木春)
  • Files
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  • approve immediately
    Date of Submission 2003-07-03

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