Image Compression Techniques Using Linear Algebra with SVD Algorithm

S. Selvam, S. Selvam
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Abstract

In recent days, the data are transformed in the form of multimedia data such as images, graphics, audio and video. Multimedia data require a huge amount of storage capacity and transmission bandwidth. Consequently, data compression is used for reducing the data redundancy and serves more storage of data. In this paper, addresses the problem (demerits) of the lossy compression of images. This proposed method is deals on SVD Power Method that overcomes the demerits of Python SVD function. In our experimental result shows superiority of proposed compression method over those of Python SVD function and some various compression techniques. In addition, the proposed method also provides different degrees of error flexibility, which give minimum of execution of time and a better image compression.
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基于SVD算法的线性代数图像压缩技术
最近,数据被转换成多媒体数据的形式,如图像、图形、音频和视频。多媒体数据需要大量的存储容量和传输带宽。因此,数据压缩用于减少数据冗余,并提供更多的数据存储。本文解决了有损图像压缩的问题(缺点)。该方法是在SVD幂次方法的基础上,克服了Python SVD函数的缺点。实验结果表明,本文提出的压缩方法优于Python奇异值分解函数和其他一些压缩技术。此外,该方法还提供了不同程度的误差灵活性,使执行时间最短,图像压缩效果更好。
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