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Wavelet-Based Image Compression Encoding Techniques - A Complete Performance Analysis

机译:基于小波的图像压缩编码技术 - 完整的性能分析

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摘要

This paper presents a complete analysis of wavelet-based image compression encoding techniques. The techniques involved in this paper are embedded zerotree wavelet (EZW), set partitioning in hierarchical trees (SPIHT), wavelet difference reduction (WDR), adaptively scanned wavelet difference reduction (ASWDR), set partitioned embedded block coder (SPECK), compression with reversible embedded wavelet (CREW) and spatial orientation tree wavelet (STW). Experiments are done by varying level of the decomposition, bits per pixel and compression ratio. The evaluation is done by taking parameters like peak signal to noise ratio (PSNR), mean square error (MSE), image quality index (IQI) and structural similarity index (SSIM), average difference (AD), normalized cross-correlation (NK), structural content (SC), maximum difference (MD), Laplacian mean squared error (LMSE) and normalized absolute error (NAE).
机译:本文介绍了基于小波的图像压缩编码技术的完整分析。 本文涉及的技术是嵌入的Zerotree小波(EZW),在分层树(SPIHT)中设置分区,小波差异减少(WDR),自适应扫描的小波差异减少(ASWDR),设置分区嵌入式块编码器(SPECK),压缩 可逆嵌入小波(船员)和空间定向树小波(STW)。 通过不同的分解水平,每像素的比特和压缩比来完成实验。 评估是通过将参数采用峰值信号的参数到噪声比(PSNR),均方误差(MSE),图像质量指数(IQI)和结构相似性指数(SSIM),平均差(AD),归一化交叉相关(NK ),结构内容(SC),最大差(MD),拉普拉斯均方误差(LMSE)和归一化绝对误差(NAE)。

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