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A method for quality assessment of parametric images based on nonlinear structural similarity deviation

A technology of structural similarity and quality evaluation, applied in the field of image processing, can solve the problems of unsatisfactory degraded image quality evaluation algorithms, etc., and achieve the effect of improving image quality evaluation, improving robustness, and good realizability

Active Publication Date: 2018-08-17
CHANGZHOU INST OF TECH
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Problems solved by technology

[0004] At present, although some simple degraded image evaluation algorithms are relatively mature, the effect of the degraded image quality evaluation algorithm caused by various factors is not ideal.

Method used

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  • A method for quality assessment of parametric images based on nonlinear structural similarity deviation
  • A method for quality assessment of parametric images based on nonlinear structural similarity deviation
  • A method for quality assessment of parametric images based on nonlinear structural similarity deviation

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Embodiment Construction

[0019] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0020] The present invention proposes a method for evaluating the quality of images with parameters based on nonlinear structure similarity deviation, which is used to evaluate the image quality of image acquisition, transmission, processing and compression. Images with different compression levels have strong effectiveness, so it is also an effective image quality assessment method. When calculating the effective features for evaluating image quality, the local gradient spectrum and edge intensity gradient spectrum are used to characterize the image, which is characterized by the effective combination of gradient spectrum and edge intensity spectrum, and the calculation is similar to the local gradient structure similarity spectrum and local edge intensity structure of the reference image. The adaptive selection can effectively characterize ...

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Abstract

The present invention discloses a quality estimation method of a parametric image based on nonlinear structural similarity deviation. Firstly the RGB color image spaces of a reference image and a degraded image are converted into a Gauss image space and a grayscale image space, then a local edge intensity spectrum and a local gradient spectrum are generated and are subjected to nonlinear normalization, the corresponding local edge similarity map and the corresponding local gradient similarity map are calculated, and finally through analyzing the structural characteristic of the local similarity map, a value with a small similarity deviation is adaptively selected to be the quality estimation value of the degraded image. According to the method, the quality estimation effect of different fuzzy, JPEG, noise and other natural images is good, the calculation is convenient and efficient, and the realizability is good.

Description

technical field [0001] The invention belongs to the field of image processing, in particular to a method for evaluating the quality of a parameterized image based on nonlinear structure similarity deviation. Background technique [0002] Different distortions may be introduced in each stage of image acquisition, storage, transmission, processing, and display. These distortions generally cause different levels of image quality degradation, making it impossible for users to select the desired image from a large number of images. Therefore, how to effectively and correctly evaluate the quality of an image has attracted the attention of many scholars. At present, there are two main categories of image quality evaluation methods: subjective evaluation methods and objective evaluation methods. Subjective evaluation is obtained after evaluation by multiple people, which is more consistent with human visual characteristics, but it is time-consuming, laborious, affected by various f...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00
CPCG06T7/0002G06T2207/30168
Inventor 相入喜朱锡芳吴峰许清泉张美凤蔡建文郭杰夏靖杰
Owner CHANGZHOU INST OF TECH
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