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Deblocking of Block-Transform Compressed Images Using Phase-Adaptive Shifted Thresholding

机译:使用相位自适应移位阈值对块变换压缩图像进行解块

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Many popular image compression schemes are based on block-transform coding, a technique where images are broken into small blocks of pixels prior to transformation and compression. Block-transform coding often introduces blocking artifacts which are particularly prevalent at low bit-rates due to quantization errors. A novel algorithm for deblocking block-transform compressed images is proposed in this paper. This algorithm is based on a phase-adaptive, shifted thresholding technique that estimates the original uncompressed image as the weighted sum of shifted versions of the decompressed image subjected to a threshold. An efficient integer transform is used to construct the shifted versions of the decompressed image. The aggregation weights are obtained adaptively using the local phase moment characteristics of the underlying image content. The proposed algorithm utilizes important human perceptual characteristics to provide effective image deblocking while preserving image detail. Experimental results show that the proposed algorithm is more efficient than comparable methods and yields both subjective results and peak signal-to-noise ratio (PSNR) results comparable to existing methods.
机译:许多流行的图像压缩方案都是基于块变换编码的,该技术是在变换和压缩之前将图像分解成小的像素块。块变换编码经常引入块伪像,由于量化误差,块伪像在低比特率下尤其普遍。提出了一种新的解块块变换压缩图像算法。该算法基于相位自适应移位阈值技术,该技术将原始未压缩图像估计为经过阈值的解压缩图像的移位版本的加权和。有效的整数变换用于构造解压缩图像的移位版本。使用基础图像内容的局部相矩特性可自适应地获得聚合权重。所提出的算法利用重要的人类感知特性来提供有效的图像去块化,同时保留图像细节。实验结果表明,所提出的算法比可比方法更有效,并且可产生与现有方法相当的主观结果和峰值信噪比(PSNR)结果。

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