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Low Bit Rate Image Coding Based on Wavelet Transform and Color Correlative Coding

机译:基于小波变换和颜色相关编码的低比特率图像编码

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Along with the rapid development of information processing, people attach more and more importance to image compression. Most coding techniques for color image compression employ a de-correlation approach, the RGB space is transformed into a de-correlation color space, then the de-correlated color components are encode separately by the same method for examples JPEG and JPEG2000. A different image encoding method of correlation and wavelet transform approach (CWA) based on human visual system, is presented in this paper. Taking into account the human visual characteristics and instead of de-correlating color components, we employ the existing-color correlation Y,G,R components, after Wavelet transform of these components, G component Wavelet Coefficient is the base component to approximate Y,R components' Wavelet Coefficient on the basis of the least linear squares. Then in order to enhance the algorithm's performance, when the Wavelet Coefficient approximation of Y,R components, different sub-band choice different size block on different sub-hand characteristics. G component Wavelet Coefficients after of quantization is encoded using adaptive Huffman coder based on different sub-band, and Huffman bit stream can be encoded using arithmetic coder. The Wavelet Coefficient approximation of Y,R components convert char stream, then is encoded using Huffman coder. Experimental results show that the proposed correlation and wavelet transform image coder based on human visual system offers coding performance superior to presently available algorithms based on the common de-correlation approach.
机译:随着信息处理的快速发展,人们将越来越重视图像压缩。用于彩色图像压缩的大多数编码技术采用去相关方法,将RGB空间变换为去相关颜色空间,然后通过相同的方法单独对去相关的颜色分量进行编码,例如JPEG和JPEG2000。本文介绍了基于人类视觉系统的相关性和小波变换方法(CWA)的不同图像编码方法。考虑到人类的视觉特性和代替去相关颜色组件,我们采用现有颜色的相关性Y,G,R分量,在这些组件的小波变换之后,G分量小波系数是近似Y,R的基本组件组件基于最小线性正方形的小波系数。然后为了提​​高算法的性能,当y,r分量的小波系数近似时,不同的子带选择不同的尺寸块在不同的副手特征上。 G分量在量化之后使用基于不同子带的自适应霍夫曼编码器进行编码之后的组件小波系数,并且可以使用算术编码器对霍夫曼比特流进行编码。 Y,R分量转换Char流的小波系数近似,然后使用Huffman编码器进行编码。实验结果表明,基于人类视觉系统的提出的相关性和小波变换图像编码器提供了优于当前可用算法的编码性能,基于常见的去相关方法。

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