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

Entropy-based double-viewpoint reference-free objective stereo-image quality evaluation method

An objective quality evaluation and stereoscopic image technology, applied in the field of image processing, to achieve accurate reflection and high consistency

Active Publication Date: 2017-05-10
TIANJIN UNIV
View PDF2 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

This patented technology proposes an objectively evaluating method that uses both visually-perceptual data (the human eye) and auditory processing techniques for better understanding how well images look good when displayed together or compared against each other. By combining this analysis into two different ways we aim at improving the accuracy and reliability of assessing stereoscopic imagery's overall appearance.

Problems solved by technology

This patents describes two technical problem addressed by this patented technique: improving the accuracy of evaluating stereoscopy images without overlooking or distorting their appearance due to incorrect processing caused by factors like perspective shading, depth blurriness, etc., which can lead to eye strain when viewed through binoculars with poor eyesight.

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
  • Entropy-based double-viewpoint reference-free objective stereo-image quality evaluation method
  • Entropy-based double-viewpoint reference-free objective stereo-image quality evaluation method
  • Entropy-based double-viewpoint reference-free objective stereo-image quality evaluation method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0017] An entropy-based method for objective evaluation of the quality of two-view no-reference stereoscopic images. Each distorted stereoscopic image pair is composed of a left image and a right image. Let the distorted image pair be (t l ,t r ), including the following steps:

[0018] Step 1: Simulate the characteristics of human vision, for distorted image pairs (t l ,t r ) of the left and right images are subjected to two-dimensional Gabor filtering to obtain the corresponding energy responses, and then convolution and processing are performed, and the weighting factors of the left and right images are obtained after normalization operations: W L (x,y) and W R ((x+d), y), where (x, y) is the pixel coordinates, (x+d) represents the parallax compensation, and d represents the abscissa difference of the pixel point for parallax compensation on the right image; the calculation method is as follows

[0019] (1) The two-dimensional Gabor filter is:

[0020]

[0021] wher...

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 an entropy-based double-viewpoint reference-free objective stereo-image quality evaluation method. The method comprises that 2D Gabor filtering is carried out on a distortion image pair to obtain a left-image weight factor and a right-image weight factor; a weighting operation is carried out to obtain a visual sensing image of the distortion image pair; K-SVD is used to implement dictionary learning; an OMP method is used for sparse representation, and a corresponding coefficient matrix C is obtained; an entropy is calculated from the coefficient matrix C after sparse representation of the visual sensing image; and SVM is used to train the entropy of the image pair in an image library and a corresponding subjective evaluation value DMOS, and a corresponding entropy-DMOS model is obtained. According to the method, double-viewpoint characteristics are taken into full consideration.

Description

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

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
Owner TIANJIN UNIV
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