A No-Reference Stereo Image Quality Evaluation Method Based on Binocular Perception

A stereoscopic image and quality evaluation technology, applied in the field of image analysis, can solve the problems of poor subjective consistency, large time and space complexity, and low performance of no-reference stereoscopic image quality evaluation technology, and achieve strong application value and subjective consistency. high sex effect

Active Publication Date: 2017-05-31
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

[0028] The purpose of the present invention is to provide a no-reference stereo natural image quality evaluation method based on binocular perception in order to solve t

Method used

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  • A No-Reference Stereo Image Quality Evaluation Method Based on Binocular Perception
  • A No-Reference Stereo Image Quality Evaluation Method Based on Binocular Perception
  • A No-Reference Stereo Image Quality Evaluation Method Based on Binocular Perception

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Embodiment

[0056] The process of this method is as follows figure 1 As shown, the specific implementation process is:

[0057] Step 1. For the left and right views of the image to be tested, calculate the disparity map d, and then calculate the information amount of the left and right views at the spatial position i respectively, and use the information to synthesize the monocular image c={c i :i∈I}. The specific calculation method is as follows:

[0058] Step 1.1, use the Gaussian mixture model to decompose the left and right views into two random fields.

[0059] v=s·u, (11)

[0060] among them, Represents the left and right views, and i is the spatial index. s={s i :i∈I} is a non-negative scale random field, Mean is 0, covariance is C u Gaussian vector.

[0061] Step 1.2, calculate the amount of information in the space position i of the left and right views

[0062]

[0063] Step 1.3, based on the binocular perception characteristics, use the information entropy of the left and right view...

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Abstract

The invention relates to an image quality evaluation method, and specifically relates to a no-reference stereo image quality evaluation method based on binocular perception, and belongs to the image analysis field. The method utilizes the left view and the right view of a distorted stereo image to calculate the parallax and the information entropy, and then the left view and the right view are respectively synthesized into a monocular image and a dot product graph. Natural scene statistical characteristics are extracted from four input images (the left view, the right view, the monocular image and the dot product graph) respectively. Quality forecasting and evaluation can be performed by using a machine learning method (such as SVM (Support Vector Machine)). The no-reference stereo image quality evaluation method is high in the subjective consistency and can be embedded into an application system related with stereo image/video processing, thus having high application value.

Description

Technical field [0001] The invention relates to an image quality evaluation method, in particular to a non-reference stereo image quality evaluation method based on binocular perception, belonging to the field of image analysis. Background technique [0002] In the past ten years or so, the number of stereoscopic image / video resources that people can access has increased dramatically. It can be said that stereo image / video resources have become civilian, popular, and trendy. With the gradual popularity of three-dimensional resources, the accompanying side effect is uneven visual quality. Stereoscopic images / videos will inevitably introduce distortion in all stages of scene acquisition, encoding, network transmission, decoding, post-processing, compression storage and projection. For example, blur distortion caused by equipment parameter settings, lens shake and other factors in the scene acquisition process; compression distortion caused by stereo image compression and storage,...

Claims

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Application Information

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IPC IPC(8): H04N17/00H04N13/00
CPCH04N13/106H04N17/00
Inventor 刘利雄刘宝黄华
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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