以小波轉換為基礎的資料壓縮方式為目前越來越熱門的課題，利用離散小波轉換Discrete Wavelet Transform (DWT)為基礎的壓縮技巧如 Embedded Zerotree Wavelet encoder (EZW)、Set Partitioning in Hierarchical (SPIHT)，其壓縮效率皆能在高壓縮率的狀況下超越原本以離散小波轉換Discrete Cosine Transform (DCT)為主的的壓縮技術。
小波轉換的資料壓縮標準中，JPEG 2000 為目前最先進的靜態影像壓縮技術，J2K使用Daubenchies 9/7作為失真壓縮的小波轉換標準。小波轉換的種類相當繁多，研究指出，各種不同的小波轉換在每張影像有不同的壓縮效果，換言之，針對每張影像可以嘗試找出其最適合的小波轉換。
本篇論文提供了一個最佳化的機制與構想，可以提升JPEG 2000與其他小波轉換的資料壓縮標準的影像品質，只要稍微修改壓縮封包的檔頭，未來可以在各種標準下實現更多不同需求、針對不同長度的小波分解做最佳化。研究結果也指出CEP可以有效的提升每個壓縮率下的影像品質，CEP最佳化的過程為了尋找最適合的小波分解係數需要花點時間，但是每一張影像只需要做一次便可隨時重現研究成果，解碼端使用者若接到CEP最佳化過的影像格式，即可迅速、確實的獲得影像品質的提升。

JPEG 2000 (J2K) is an international standard for still image compression, which is based on wavelet transformation and adopts the Daubenchies 9/7 filter for lossy compression. Considering that a wavelet filter might be suitable for one image but not for the other in regard to reconstruction quality, in this thesis, we propose a novel filter design framework based on the Daubenchies 9/7 filter, which employs chaos evolution programming (CEP) to optimize the wavelet filter for each specific image. The customized filter design is ready to incorporate into the J2K codec since the filter coefficients can be constructed with only one single parameter, which can be easily packaged into the J2K header. Experimental results show that CEP-trained filters achieve higher image quality.

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