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Full-reference mixed-distortion image quality evaluation method based on sparse decomposition residuals

A Distorted Image, Sparse Decomposition Technique

Active Publication Date: 2018-01-16
TIANJIN UNIV
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Problems solved by technology

[0004] The present invention aims at the problem that the objective quality evaluation method based on sparse representation is only effective for single distortion types and only considers sparse coefficients for quality evaluation, and proposes a full-reference image quality evaluation method suitable for evaluating mixed distortion images

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  • Full-reference mixed-distortion image quality evaluation method based on sparse decomposition residuals
  • Full-reference mixed-distortion image quality evaluation method based on sparse decomposition residuals
  • Full-reference mixed-distortion image quality evaluation method based on sparse decomposition residuals

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Embodiment Construction

[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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Abstract

The invention relates to a full-reference mixed-distortion image quality evaluation method based on sparse decomposition residuals. The method comprises steps: a natural image is selected, and image blocks are selected from the natural image as training image blocks to train a dictionary D; a sparse decomposition residual energy graph is acquired; and the image distortion level is evaluated basedon the sparse decomposition residual energy graph. The third step comprises the following sub steps: the local residual energy feature similarity is calculated; a variogram solved by a reference imageis used as a weight to acquire a local residual mass fraction Qrl; a global residual Gres<r> is solved by the local residual energy graph; the mass fraction of the global residual feature is calculated; and the local residual mass fraction Qrl and the global residual mass fraction Qrg are integrated to obtain the evaluation mass fraction Qr of the final residual feature.

Description

technical field [0001] The invention belongs to the field of image processing, in particular to an objective evaluation system for plane images, and relates to a full-reference mixed distortion image quality evaluation method. Background technique [0002] With the development of digital image processing technology, image quality evaluation technology has become a research hotspot in the field of image processing. Image quality evaluation methods can be divided into two categories: subjective evaluation and objective evaluation. The former evaluates the quality of objects based on people's subjective feelings, while the latter gives quantitative indicators through mathematical modeling, simulating the human visual perception mechanism to measure the quality of images. Although subjective evaluation has high reliability, it is expensive, time-consuming, and difficult to operate. Therefore, objective evaluation methods have attracted more attention from scholars. According t...

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Application Information

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IPC IPC(8): G06T7/00
Inventor 冯丹丹侯春萍岳广辉马彤彤刘月
Owner TIANJIN UNIV
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