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研究生:廖志豪
研究生(外文):Zhi-Hor Liao
論文名稱:高灰階影像區塊表示之快速動差值計算
論文名稱(外文):FAST COMPUTATION OF MOMENTS ON COMPRESSED GREY IMAGES USING BLOCK REPRESENTATION
指導教授:鍾國亮鍾國亮引用關係
指導教授(外文):Kuo-Liang Chung
學位類別:碩士
校院名稱:國立臺灣科技大學
系所名稱:資訊管理系
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2001
畢業學年度:89
語文別:英文
論文頁數:37
中文關鍵詞:演算法區塊表示壓縮影像處理動差值S-treeShading
外文關鍵詞:AlgorithmBlock RepresentationCompressionImage ProcessingMomentsS-treeShading
相關次數:
  • 被引用被引用:1
  • 點閱點閱:448
  • 評分評分:
  • 下載下載:18
  • 收藏至我的研究室書目清單書目收藏:1
在影像處理中,我們可以利用其動差量來做影像幾何分析。假設輸入一張大小為 NxN 的高灰階影像,我們使用了空間資料結構的壓縮方法將影像切成 K 個區塊且 K<(N^2)。本篇論文主要是提供一個時間複雜度為 O(N x sqrt(K)) 的快速有效率方法來直接在壓縮的影像上求出動差量。實驗結果顯示本篇論文所提出的方法其不僅可以節省計算時間,且在一定的壓縮比例上其亦能很精確的求出其動差量值。
In image processing, moments are useful tools for analyzing shapes. Suppose the input grey image with size NxN has been compressed into the compressed image using the block representation, where the number of blocks used is K, commonly K < (N^2) due to the compression effect. This theme presents an efficient O(N sqrt(K))--time algorithm for computing moments on the compressed image directly. Experimental results reveal a significant computational advantage of the proposed algorithm while preserving a high accuracy of moments and good compression ratio.
目錄
中文摘要------------------------------------ I
英文摘要------------------------------------ II
誌 謝------------------------------------III
圖表索引------------------------------------ V
1. INTRODUCTION---------------------------- 1
2. PRELIMINARY----------------------------- 4
3. COMPRESSED IMAGES----------------------- 5
4. COMPUTING MOMENTS ON COMPRESSED IMAGES-- 10
5. EXPERIMENTAL RESULTS-------------------- 19
6. CONCLUSIONS----------------------------- 23
7. REFERENCES------------------------------ 24
8. APPEBDIX 1------------------------------ 27
9. APPENDIX 2------------------------------ 30
10. 作者簡介-------------------------------- 32
11. 授權書---------------------------------- 33
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I. M. Spiliotis and B. G. Mertzios, ''Real--time computation of two--dimensional moments on binary images using image block representation,'''' IEEE Trans. on Image Processing, Vol. 7, No. 11, pp. 1609-1615, 1998.
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