以小波轉換為基礎的彩色文件圖文分割與高倍率影像壓縮法之研究

Abstract

利用小波轉換能將影像訊號切割成若干個互相可以預測的頻帶，因而 對低頻影像可以達到高壓縮率的目的；對高頻影像則會有邊界模糊的現象 。所以我們提出圖文分割的方法，改善模糊的現象。本篇論文是利用圖文 分割的技巧，在小波轉換後的係數中，分離彩色文件影像中的圖形區域和 文字區域，將圖形部分交由零樹去編碼，而文字部分則用多重平面彩色文 字壓縮法來編碼，用以解決文字邊界模糊的情形。圖文分割的方法，主要 是利用顏色數目、區塊投影變異數比和碎形維度三項參數在圖形與文字上 的特性不同來加以判斷的。因為這三項參數的特性有很強的模糊性質，所 以我們也發展了一套適合圖文分割的模糊規則演算法。最後實驗結果證明 ，圖文分割與影像壓縮法的組合，很適合拿來做高倍率的彩色文件影像壓 縮。 另外本文也討論了彩色影像如何決定最佳位元分配率的問題、小 波轉換切割層數與PSNR的關係、高頻小波係數對影像品質的影響。 In this thesis, we use the technology of graph and text segmentationin wavelet coefficients to separate graph and text in color document. Zero-Tree encodes the part of graph-image, and the part of text-image is coded by the method of multi-plain text coding. Color-number, the ratio of projection variance, and fractal dimension which are different in graph and text part of the block give us the information manipulate the segmentation. Because of the characteristic of these three parameters which reveal strong fuzzy property, we develop a fuzzy rule to achieve the purpose of segmentation. The result of program simulation shows that image compression with graph- text segmentation has good performance on high compression ratio in color document. We also discuss the problem of the best bit- rate allocation in color image, the relation between PSNR and the layer number in wavelet transform, and how high-frequency coefficients effect the image quality.