近代因為數位革命，我們將許多自然界現象運用數位的描述加以處理。然而，影像因數值化造成龐大資料量，無論在儲存或是交換上都造成困擾。將影像透過各種方式予以壓縮，成為現今經常被探討的課題。另一方面，將既有的影像放大，使它盡可能的符合真實、自然，卻往往因為硬體限制，許多影像增強的作業轉而採用數位影像處理。然而，看起來似乎是不相關的兩件事情卻是有所關聯的。對於較好的影像放大技術，我們往往可以拿來作為預測編碼用，進而達到更高的影像壓縮率。
近年來，小波轉換被廣泛的運用在許多地方，因為它可以將一個複雜的訊號分析其特性，分成許多不同的子訊號。對於不同性質的子訊號，我們可以依照需要，加以區別處理。我們利用小波解析的方法，探討自然影像透過小波解析後，低頻訊號與高頻訊號的關聯。利用估測出的高頻訊號將影像加以放大，並比較其差異。進一步地，我們在運用小波解析的漸進可調式編碼法中，將其原本應編碼的高頻訊號加以代換，改為編碼透過低頻訊號預測後結果與原值之間的誤差值。透過我們預測的結果，影像可以再壓縮的更小，亦能夠不失其原本漸進可調式編碼的特性。
綜合兩分面，我們可以在傳統的編碼法上，除了在得到相同的資訊量下擁有相同的畫質之外，還可以進一步的降低我們的位元率。

Due to hardware limitation, most interpolation method has been carried out by software and becomes an important research task. Various techniques have been proposed to improve the visual quality of interpolated quality. In addition, with a good interpolation, we can facilitate predictive image coding technique.
Wavelets are being used in a number of different applications such as image enlargement and image compression. In order to benefit both applications, we propose a method to estimate high pass output from the low pass one. Using the predicted high pass output, we would be able to enlarge the image superior to other compared interpolation methods in many situations. Moreover, we use the predicted subband to wavelet image coder. It is shown that by using the proposed method, we can profit both image enlargement and its compression.

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