Full-reference mixed-distortion image quality evaluation method based on sparse decomposition residuals
A Distorted Image, Sparse Decomposition Technique
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[0019] The present invention will be further elaborated below in conjunction with the accompanying drawings.
[0020] The present invention first conducts dictionary training, and then performs image quality assessment based on sparse decomposition residuals. The specific method is as follows:
[0021] The first step is to select natural images for training. Here, 10 images are selected for dictionary training. Before performing dictionary training and quality evaluation, in order to eliminate the influence of image content, the present invention firstly performs normalization processing on images. In the dictionary training part, 10,000 8×8 image blocks are randomly selected from the training images as training image blocks.
[0022] The second step is to train the dictionary. Combine each image block in the training image block into a training sample set Y=[y 1 ,y 2 ,...,y p ]∈R n×P , where each image block y p ∈ R n×1 ,p=1,2,...,P contains n pixels, where n=64, P=10...
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