藉由調變式區域成長及假輪廓消除技巧而得的彩色影像壓縮技術

Abstract

在本論文中，我們提出了一個切割式的彩色影像壓縮方法。首先，我們用 由下而上的四分樹切割來分出區塊，並以調變式區域成長法加以結合。之 後，再對切割出來的區塊輪廓與紋理加以編碼。我們以雙變數多項式函數 來表示區塊的紋理，用鍊式編碼來對區塊輪廓編碼。最後，在重建回來的 影像中有些許失真，我們先偵測出假輪廓再用我們提出的平滑化處理，以 得到更佳的影像。實驗結果顯示，大部份的複雜紋理都可以被重建回來， 而且後處理過也可改善影像品質。 In this thesis, we propose a segmentation-based compression method for color images. First, we split the image by bottom-up quadtree decomposition, and then merge by adaptive region growing. After that, the contours and textures of the segmented regions are encoded. We encode the region texture by polynomial approximation, and encode the region contour using chain code. Finally, because there are some distortion in the reconstructed images, we detect the false contours and apply our smoothing algorithm to get a better image. Experimental results show that most of the complex texture can be reconstructed, and after the postprocessing we can usually have a better image quality.