Non-reference high-dynamic range image objective quality evaluation method

A high dynamic range, evaluation method technology, applied in image communication, television, electrical components, etc., can solve problems such as only considering luminance distortion, ignoring chromaticity distortion, and human visual perception inconsistency

Active Publication Date: 2018-07-24
NINGBO UNIV
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Problems solved by technology

[0005] An excellent objective quality evaluation method for high dynamic range images should be able to well reflect the characteristics of human visual perception. Reference objective quality eva

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  • Non-reference high-dynamic range image objective quality evaluation method
  • Non-reference high-dynamic range image objective quality evaluation method
  • Non-reference high-dynamic range image objective quality evaluation method

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[0023] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0024] A no-reference high dynamic range image objective quality evaluation method proposed by the present invention, its overall realization block diagram is as follows figure 1 shown, which includes the following steps:

[0025] ① Denote the distorted high dynamic range color image to be evaluated as I dis; Then using existing technology to I dis Expressed in the form of a third-order tensor, denoted as V dis ; Then use the existing tensor Tucker3 decomposition algorithm to V dis Perform 3-mode product operation to get V dis The kernel tensor of , denoted as G dis ; then G dis The 1st channel acts as the I dis The first feature image of , denoted as G dis1 ; and G dis The 2nd channel serves as the I dis The second feature image of , denoted as G dis2 ; put G dis The 3rd channel serves as the I dis The third feature image of , de...

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Abstract

The invention discloses a non-reference high-dynamic range image objective quality evaluation method. The method comprises the following steps: representing an image as third-order tensor, performingtensor decomposition on a distorted high-dynamic range image by using a Tucker decomposition algorithm in the tensor decomposition since the chromaticity information has important effect in the high-dynamic range image quality evaluation, thereby obtaining a first channel integrated with the brightness distortion and the chromaticity distortion as a first feature image; extracting distortion information on the first feature image, wherein the first feature image further comprises the distortion of the chromaticity channel in comparison with the way of extracting the distortion information onlyon the brightness channel, the data size is same as that of the brightness channel, and the additional data size cannot be increased; and combining a tensor domain sensing feature vector extracted from the first feature image with a support vector regressive training model to obtain an objective quality evaluation value of the distorted high-dynamic range image. Therefore, the objective quality evaluation of the non-reference high-dynamic range image is realized, the evaluation effect is obviously improved without using the reference image.

Description

technical field [0001] The invention relates to an image quality evaluation method, in particular to an objective quality evaluation method for a high dynamic range image without reference based on tensor domain perceptual features. Background technique [0002] The development of high dynamic range (High Dynamic Range, HDR) imaging technology has changed the traditional image display method, which can bring people a more realistic visual experience. However, in the process of image acquisition, compression, storage and transmission, degradation will inevitably be introduced. Image quality directly reflects the quality of user experience, and it is the common desire of image consumers to reduce or even completely eliminate degradation. Research on the quality evaluation of high dynamic range images can effectively help solve some degradation problems. [0003] Image quality evaluation can be divided into subjective quality evaluation method and objective quality evaluation ...

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Application Information

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IPC IPC(8): H04N17/00
Inventor 郁梅邹良涛蒋刚毅陈芬彭宗举
Owner NINGBO UNIV
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