本論文提出一種基於升級機制的嶄新5/3和9/7小波轉換影像插值法以達到高品質的影像壓縮目的，並且針對個別影像提出進化規劃演算法做最佳化處理以進一步提升影像壓縮的品質。基於小波轉換後的低頻係數，本篇論文提出預測型演算法以預測將原始影像作小波轉換後的高頻係數，所以使用本文所提的預測型演算法得以將小波轉換後的低頻影像重建為原始影像，以達到影像壓縮的目的。由於奇數長度的小波濾波器其正中心係數主宰了小波轉換與反轉換的性能，所以對濾波後的小波係數做奇數或偶數的降階取樣會影響到原始影像的重建品質。因此，本篇論文在建構升級機制的奇數長度小波濾波器的低頻係數中，分別對原始影像的奇數和偶數像素做小波轉換。接著，在兩者之中選擇較好的那一個以匹配奇數小波濾波器(5/3和9/7)和原始影像的特性，以達到高品質的影像壓縮。為了更進一步改進原始影像的重建品質和驗證上述所提的演算法的最佳化程度，本篇論文同時提出了基於進化規劃演算法的影像插值法。經由實驗結果顯示，本篇論文提出的使用或不使用進化規劃的預測型演算法表現得比其它文獻所呈現的標準方法好，而且在不使用進化規劃的預測型演算法其時間複雜度也在可以接受的範圍內。

Novel 5/3 and 9/7 wavelet-based image interpolations in lifting structures with/without involving the evolutionary programming (EP) for image compression are proposed in this paper. Based on the low-band wavelet coefficients, the proposed prediction algorithms estimate high-frequency wavelet coefficients of the original image, so the original image can be reconstructed from the low-band image by using the proposed prediction algorithms. Due to the characteristics of the odd-length wavelet filter which is dominated by the intermediate coefficient, taking even or odd downsampling of the filtered coefficients significantly dominants the image reconstruction performance. Therefore, constructing the low-band wavelet coefficients through the odd-length wavelet filter in lifting structure based on even and odd pixels of the original image are respectively performed in this paper. Then, select the better one to fit the characteristics of the odd-length wavelet filters such as 5/3 and 9/7 filters and the pre-specified image for high performance image compression. To further improve the reconstruction performance and show the optimality of the above-mentioned proposed algorithms, the EP-based image interpolations are also presented in this paper. The proposed prediction algorithms with/without EP outperform other standard methods, and the computational complexity without EP is also acceptable in the experimental results.

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