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Image Quality Assessment Based on Included Angle Cosine and Discrete 2-D Wavelet Transform

机译:基于夹角余弦和离散二维小波变换的图像质量评估

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In this paper, a novel image quality assessment based on the characteristics of wavelet coefficients of images and included angle cosine is proposed. Firstly, the normal image and the images assessed are decomposed into several levels by means of wavelet transform respectively. Secondly, the approximation and detail coefficients of normal image are as the referenced sequences and the approximation and detail coefficients of the images assessed are as the comparative sequences respectively. And the included angle cosine values are calculated between the referenced sequences and the comparative sequences respectively. Moreover, image quality assessment matrix of every image assessed can be constructed based on the included angle cosine values and image quality can be assessed. The algorithm makes full use of perfect integral comparison mechanism of included angle cosine and the well matching of discrete wavelet transform with multi-channel model of human visual system. Experimental results show that the proposed algorithm can not only evaluate the integral and detail quality of image fidelity accurately but also bears more consistency with the human visual system than the traditional method PSNR.
机译:提出了一种基于图像小波系数和夹角余弦的图像质量评估方法。首先,分别通过小波变换将正常图像和评估的图像分解为几个级别。其次,正常图像的近似系数和细节系数分别作为参考序列,被评估图像的近似系数和细节系数分别作为比较序列。并且分别在参考序列和比较序列之间计算夹角余弦值。此外,可以基于所包括的角度余弦值构造每个被评估图像的图像质量评估矩阵,并且可以评估图像质量。该算法充分利用了夹角余弦的完美积分比较机制,以及离散小波变换与人眼视觉系统多通道模型的良好匹配。实验结果表明,与传统的PSNR方法相比,该算法不仅可以准确评估图像保真度的整体和细节质量,而且与人的视觉系统具有更好的一致性。

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