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Two-Dimensional Wavelet and DCT Transforms Applied for Entropic Compression Improvement Using Digital Images

机译:二维小波和DCT变换在数字图像熵压缩中的应用

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摘要

An image processing patent technique for the improvement of entropic compression with digital images has been presented. "Two-dimension wavelet transform" (2D-DWT), "two-dimension discrete cosine transform" (2D-DCT) and multi-resolution perfect reconstruction structures, with quincunx filter and grid are used for image processing and simulations using MATLAB, up to 2-level of analysis and synthesis. The possibility of suppressing the high and middle frequencies components in order to increase compression rates was considered. As a result, higher rates of entropic compression were obtained with the application of 2D-DCT after 2D-DWT in the sub-images generated from the multiresolution perfect reconstruction structures. High quality reconstructed images were obtained, even when high and middle frequencies components were suppressed.
机译:已经提出了一种用于改善数字图像的熵压缩的图像处理专利技术。 “二维小波变换”(2D-DWT),“二维离散余弦变换”(2D-DCT)和具有梅花形滤波器和网格的多分辨率完美重构结构用于使用MATLAB进行图像处理和模拟,进行2级分析和综合。考虑了抑制高频分量和中频分量以增加压缩率的可能性。结果,在多分辨率完美重建结构生成的子图像中,在2D-DWT之后应用2D-DCT,可获得更高的熵压缩率。即使抑制了高频和中频分量,也可以获得高质量的重建图像。

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