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Continuous wavelet transform-based no-reference quality assessment of deblocked images

机译:基于连续小波变换的解块图像无参考质量评估

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An image when passed through a compression process either gains noise or loses some information, resulting in a degraded image. JPEG is considered to be one of the most commonly used compression standards whose resulting images are found to be subjected to blocking artifacts at low bit rates. There exist a few deblocking algorithms which have been proposed in the literature to reduce the blocking artifacts in compressed images. However, unfortunately these deblocking techniques introduce blur distortion in the images and hence the deblocked images may contain multiple distortions. Existing image quality metrics have limitations in evaluating the quality of deblocked images as they are not designed for multiply distorted images. To overcome this issue, we propose a no-reference quality assessment technique for deblocked images using continuous wavelet transform. We evaluate the proposed technique on DBID database which consists of general deblocked images. Experimental results show that the proposed quality assessment technique outperforms the existing image quality assessment techniques for deblocked images.
机译:图像经过压缩处理后会获得噪音或丢失一些信息,从而导致图像质量下降。 JPEG被认为是最常用的压缩标准之一,发现其压缩后的图像在低比特率下会受到块状伪影的影响。在文献中已经提出了一些去块算法,以减少压缩图像中的块伪像。但是,不幸的是,这些解块技术在图像中引入了模糊失真,因此解块后的图像可能包含多个失真。现有的图像质量度量标准在评估解块图像的质量时存在局限性,因为它们不是为多重失真的图像而设计的。为了克服这个问题,我们提出了一种使用连续小波变换的去块图像无参考质量评估技术。我们在由一般的解块图像组成的DBID数据库上评估提出的技术。实验结果表明,所提出的质量评估技术优于去块图像的现有图像质量评估技术。

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