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Image Compression based on Block Truncation Coding using Clifford Algebra

机译:基于块截断编码的图像压缩使用Clifford代数

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The Block Truncation Coding (BTC) is one of the lossy image compression algorithm in which first and second order moments are preserved in each image block. The present work investigates image compression based on Absolute Moment Block Truncation Coding (AMBTC) and Clifford Algebra. Here we develop a technique to express a positive integer as a sum of largest perfect square of positive integer. The largest square is computed from the given integer, and then the same process is repeated from the residual part of the integer successively. The proposed method gives very good performance in terms of PSNR values when compared to the conventional BTC and AMBTC. To assess image quality some parametric measures bring into service such as: Peak Signal to Noise Ratio (PSNR), Weighted Peak Signal to Noise Ratio (WPSNR), Bit Rate (BR), and Structural SIMilarity Index (SS1M). The comparative result shows that proposed algorithm is the better than BTC and AMBTC.
机译:块截断编码(BTC)是其中第一和二阶矩保留在每个图像块中的损失图像压缩算法之一。本工作基于绝对时刻块截断编码(AMBTC)和Clifford代数来调查图像压缩。在这里,我们开发一种技术来表达正整数作为正整数的最大完美广场的总和。从给定的整数计算最大正方形,然后连续地从整数的剩余部分重复相同的过程。当与传统的BTC和AMBTC相比,所提出的方法在PSNR值方面提供了非常好的性能。为了评估图像质量,一些参数措施将诸如:峰值信号到噪声比(PSNR),加权峰值信号到噪声比(WPSNR),比特率(BR)和结构相似性指数(SS1M​​)。比较结果表明,所提出的算法比BTC和AMBTC更好。

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