Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

No-reference stereo image quality assessment method based on visual perception and binocular competition

A technology of visual perception and binocular competition, applied in the field of stereo image quality evaluation, based on visual perception and binocular competition without reference stereo image quality evaluation, it can solve problems such as poor algorithm stability, poor subjective consistency, poor database independence, etc. Achieve the effects of high database independence, high subjective consistency, and high algorithm stability

Active Publication Date: 2019-03-19
BEIJING INSTITUTE OF TECHNOLOGYGY
View PDF1 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0019] The purpose of the present invention is to solve the problems that the simulation method of the human visual perception system is not perfect enough, the visual perception information in the image is not fully utilized, the subjective consistency is poor, the independence of the database is poor, and the algorithm stability is poor, etc. in the quality evaluation of the stereoscopic image without reference. A No-Reference Stereo Image Quality Evaluation Method Based on Visual Perception and Binocular Competition

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • No-reference stereo image quality assessment method based on visual perception and binocular competition
  • No-reference stereo image quality assessment method based on visual perception and binocular competition
  • No-reference stereo image quality assessment method based on visual perception and binocular competition

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0046] The procedure of this method is as follows figure 1 As shown, the specific implementation process is:

[0047] Step 1: Convert the input stereo image pair to be tested into grayscale information.

[0048] Step 2: applying a matching algorithm to further process the grayscale information to obtain a simulated disparity map and an uncertainty map, and at the same time using Gabor filtering to obtain a filter response of the grayscale information.

[0049] The simulated disparity map is obtained by matching the structural similarity of the gray information of the left and right views.

[0050] The uncertainty map is calculated as follows:

[0051]

[0052] Among them, l represents the grayscale image of the left view, r represents the grayscale image of the right view after parallax compensation processing, μ and σ represent the mean value and standard deviation of the corresponding grayscale image respectively, and C 1 and C 2 represent constant terms, respectively...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to a stereo image quality evaluation method, in particular relates to a non-reference stereo image quality evaluation method based on visual perception and binocular rivalry, andbelongs to the field of the image analysis. The method comprises the following steps: firstly converting an input stereo image pair into gray information, obtaining an simulated parallax graph and anuncertainty graph of the stereo image pair through the gray information by using a matching algorithm, and synthesizing a monocular image by using the gray information and the filter response and simulated parallax graph correction thereof; secondly, performing Gauss differential processing on the obtained monocular image and the uncertainty graph on different scale spaces and frequency spaces, and extracting natural scene statistical and a visual perception feature vector; and then respectively training the feature by using a support vector machine and a BP neural network to obtain a prediction model, and performing the quality prediction and evaluation by using the prediction module and the testing and the corresponding feature vector. The method disclosed by the invention has the characteristics of being high in subjective consistency, high database independence, and high stability, and presents competitive effect when processing multiple distortion types, can be embedded into an application system related to a stereo image / video processing and like stereo visual content, and has strong application value.

Description

technical field [0001] The invention relates to a method for evaluating the quality of a stereoscopic image, in particular to a method for evaluating the quality of a stereoscopic image without reference based on visual perception and binocular competition, and belongs to the field of image analysis. Background technique [0002] In recent years, with the development of science and technology, the cost of stereoscopic image generation and dissemination has become lower and lower, which makes stereoscopic images, as an excellent medium of information dissemination, more and more popular in our daily life. Universal and increasingly indispensable. However, stereoscopic images will inevitably introduce distortion in each stage of scene acquisition, encoding, network transmission, decoding, post-processing, compression storage and projection. Blurring distortion; compression distortion caused by image compression storage, etc. The introduction of distortion will greatly reduce...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): H04N17/00
Inventor 刘利雄张久发王天舒黄华
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products