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A novel non-customary method of image compression based on image spectrum
Sādhanā ( IF 1.6 ) Pub Date : 2020-11-19 , DOI: 10.1007/s12046-020-01519-7
Himanshu Kumar , Sumana Gupta , K S Venkatesh

Compression of multimedia content is an important processing step and backbone of real life applications in terms of optimum resource utilization in transmission and storage. It is an established field of research with very little scope for further improvement in achieved compression through customary coding-based compression techniques. Consequently, non-customary compression methods have become an important area for future research. Based on the principle ‘Any information that can be restored can be compressed’, we propose a novel spectrum-based image compression technique to further reduce the data footprint with satisfactory quality metric for images. We first blur the image with a point spread function (PSF) determined using frequency content of the given image. Blurring increases the DC component in the image, which in turn gets further compressed compared with original image by DCT-based JPEG compression. To recover the image, we perform deconvolution using the known blur PSF. Results obtained show further improvement of \(20-30\%\) in achieved compression with respect to original JPEG compressed image with satisfactory quality of recovered image.



中文翻译:

基于光谱的非常规图像压缩新方法

就传输和存储中的最佳资源利用而言,多媒体内容的压缩是重要的处理步骤和现实生活中应用程序的主干。这是一个已经建立的研究领域,通过常规的基于编码的压缩技术来进一步改善已实现的压缩的范围很小。因此,非常规压缩方法已成为未来研究的重要领域。基于“可以还原的任何信息都可以压缩”的原则,我们提出了一种基于频谱的新颖图像压缩技术,以令人满意的图像质量度量进一步减少数据占用量。我们首先使用点扩散函数(PSF)对图像进行模糊处理,该函数使用给定图像的频率内容确定。模糊会增加图像中的直流分量,与基于DCT的JPEG压缩相比,与原始图像相比,该压缩又得到了进一步压缩。为了恢复图像,我们使用已知的模糊PSF执行反卷积。获得的结果表明,相对于原始JPEG压缩图像实现了(20-30 \%\)的压缩,具有令人满意的恢复图像质量。

更新日期:2020-11-19
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