在本論文的研究中，我們提出以整數小波 (integer wavelet) 和灰色理
論 (grey theory) 為基礎的漸進式影像壓縮技術。在漸進式壓縮方面，我們以小波分解技術來產生不同解析度及不同波段 (subband) 的影像。同時配合灰色理論在高頻波段上做預測以達到更高的壓縮倍率。有別於傳
統影像壓縮技術由左而右由上而下的編碼。在網路瀏覽時可能因為網路
頻寬的限制而只能瀏覽半張影像。而我們所提出的方法可以因為頻寬的
限制而看到相較原始影像二分之一解析度的影像而不是只看到半張影
像，如此在瀏覽資料量較大的影像或是頻寬壅塞時更有利於上線的使用者。

In this paper a progressive image compression approach based on
our proposed integer wavelet transform and grey prediction is proposed.
The integer wavelet transform is based on a reversible round-off linear
transform algorithm to forward and backward transform integers without
any loss. The proposed compression approach is combining the EZW
method and a grey prediction to compress images. EZW is a famous
wavelet-based image compression and the grey prediction is based on
the grey theory to further improve the compression rate without
degrading the image quality. The proposed approach is suitable for
browsing large-scaled images. Several experiments and comparisons are
conducted to evaluate the performance of the proposed approach.

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