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Singular Value Decomposition Approach to Digital Image Lossy Compression

机译:数字图像有损压缩的奇异值分解方法

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The task of digital image compression is the subject of many researches for many years. Up to now this task remains a topic of constant interest. The reason of such interest is that digital media and digital communication are becoming of growing significance worldwide. The subject of this paper is a new original approach to digital image compression. It is based on using singular value decomposition of the image matrix that makes it possible to represent an image as a sum of the most significant layers (MSL). Based on this idea, a new format for image coding is developed. It makes use (1) the MSLs, which are computed according to a simple formal criterion, (2) segmentation of the image into small blocks; (3) special quantization and (4) optimal encoding of singular vectors of the preserved layers. The developed format of image coding makes it possible to achieve up to 15% rate of compression preserving high quality of the uncompressed image. The approach was validated by simulation many images. The software tool implementing the proposed technique was developed. It was used for validation of the paper results.
机译:数字图像压缩的任务是多年来许多研究的主题。到目前为止,此任务仍然是一个不断兴趣的主题。这种兴趣的原因是数字媒体和数字沟通在全球范围内变得越来越重要。本文的主题是数字图像压缩的新原始方法。基于使用图像矩阵的奇异值分解,使得可以将图像表示为最高显着层(MSL)的总和。基于此思想,开发了一种用于图像编码的新格式。它使用(1)根据简单的正式标准计算的MSLS,(2)图像分为小块; (3)特殊量化和(4)保存层的奇异载体的最佳编码。图像编码的开发格式使得可以实现高达15%的压缩速率,这些压缩率保持高质量的未压缩图像。通过模拟许多图像验证了该方法。开发了实现所提出的技术的软件工具。它用于验证纸张结果。

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