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Image Quality Assessment Based on Mutual Information in Pixel Domain

机译:基于像素域的相互信息的图像质量评估

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摘要

The natural scene statistics (NSS) model is widely used in image quality assessment algorithms, the NSS based features in frequency domain provide a good approximation to image structure, but not to the image content. To get a metric which is effectively to both structural distortion and content distortion, a new image quality assessment framework in image pixel domain based on mutual information is proposed. First, a non-overlapping segmentation set is acquired to establish the relation with image pixels. Second, the saliency and specific information are measured to catch the image content changes, and entanglement to the image structure change. Finally, the differences of image content and structural information are used to measure image quality. The experimental results show that the proposed framework has good consistency with subjective perception values.
机译:自然场景统计(NSS)模型广泛用于图像质量评估算法,频域的NSS基于的特征提供了对图像结构的良好近似,而不是图像内容。为了获得有效地实现结构失真和内容失真的度量,提出了基于相互信息的图像像素域中的新图像质量评估框架。首先,获取非重叠分割集以与图像像素建立关系。其次,测量显着性和特定信息以捕获图像内容的变化,并缠绕到图像结构变化。最后,使用图像内容和结构信息的差异来测量图像质量。实验结果表明,该框架具有与主观感知值的良好一致性。

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