基于整數(shù)小波變換和改進(jìn)嵌入零樹編碼的圖像壓縮
Image Compression Based on Integer Wavelet Transform and Improved Embedded Zerotree Wavelet Encoding
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摘要: 整數(shù)小波變換(IWT)具有輸入輸出都是整數(shù)、只需進(jìn)行位內(nèi)運(yùn)算、便于硬件實現(xiàn)等優(yōu)點，特別適于圖像的無損壓縮；而在有損壓縮方面，其效果通常稍遜于傳統(tǒng)的離散小波變換(DWT)。為了提高IWT圖像有損壓縮的性能，該文采用基于提升格式的IWT，結(jié)合基于形態(tài)膨脹運(yùn)算的改進(jìn)嵌入零樹小波編碼(EZW)方法。實驗結(jié)果表明，在沒有增加運(yùn)算復(fù)雜度的情況下，此算法與傳統(tǒng)的DWT相比，提高了峰值信噪比(PSNR)，具有較好的有損壓縮效果。
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關(guān)鍵詞:
- 整數(shù)小波變換; 嵌入零樹小波編碼; 形態(tài)運(yùn)算; 圖像壓縮
Abstract: The main advantages of Integer Wavelet Transform(IWT) are that the input and output values are all integers, all operations can be done in place, only a small memory is required and easy to be implemented in hardware. In the context of image coding, IWT is well suited for lossless compression. However, it performs a little worse compared to the conventional Discrete Wavelet Transform(DWT) for lossy compression. In this paper, a new algorithm is proposed for improving lossy compression performance of IWT, It is by means of the IWT based on lifting scheme combining with improved Embedded Zerotree Wavelet(EZW) based on morphological dilation operation. Simulation results show the proposed algorithm improves the Peak Signal Noise Ratio(PSNR) compared to conventional DWT without increasing computational complexity. -
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