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A Disparity Estimation Method Based on Improved Adaptive Weighting and Confidence Propagation

A technology of adaptive weighting and confidence propagation, applied in computing, image data processing, instruments, etc., can solve problems such as inaccurate evaluation of parallax planes, large amount of calculation for high-precision matching algorithms, and low matching accuracy

Inactive Publication Date: 2017-01-25
HARBIN NORMAL UNIVERSITY
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Problems solved by technology

[0005] The purpose of the present invention is to provide a disparity estimation method based on improved adaptive weighting and confidence propagation to solve the problem of low matching accuracy of disparity calculated by existing matching algorithms in occluded areas and depth discontinuous areas; high-precision matching algorithm The amount of calculation is large, and the implementability is poor; the problem of inaccurate evaluation of the disparity plane based on segmentation refinement method

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  • A Disparity Estimation Method Based on Improved Adaptive Weighting and Confidence Propagation
  • A Disparity Estimation Method Based on Improved Adaptive Weighting and Confidence Propagation
  • A Disparity Estimation Method Based on Improved Adaptive Weighting and Confidence Propagation

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specific Embodiment approach 1

[0041] Embodiment 1: A disparity estimation method based on improved adaptive weighting and confidence propagation according to the present invention includes the following steps:

[0042] Step 1. Calculate the correlation value C between matching pixels by using the weighted grade transformation method L ;

[0043] Step 2. Use the left-right consistency detection method to detect the occluded pixels in the image, and use the improved automatic

[0044] The adaptive weighting method is used to re-match the occluded pixels to generate the initial disparity map D 1 and the initial correlation value C 1 ;

[0045] Among them, the improvement process of the adaptive weighting method is as follows:

[0046] Suppose f(x,y) represents a certain point in the reference image, f(x+i,y+j) represents the pixels in the matching window centered on the pixel f(x,y), and the calculation of the pixel weight in the window is as follows: (1) as shown:

[0047] W ...

specific Embodiment approach 2

[0067] Embodiment 2: The difference between this embodiment and Embodiment 1 is that the process of re-matching the occluded pixels described in step 2 is:

[0068] The calculation of the initial matching cost of the reference matching window and the target matching window is shown in formula (6):

[0069] TAD x , y , d ( i , j ) = min { Σ c ∈ { RGB } | f c ( x + i , y + j ) - g c ( x - d + i , y + j ) | , δ aw }...

specific Embodiment approach 3

[0080] Specific embodiment three: the difference between this embodiment and specific embodiment one is: the process of calculating the pixel weight of the target window described in step two is:

[0081] Calculate the Euclidean distance between the central pixel g(x-d,y) of the target window and the surrounding pixels g(x-d+i,y+j) in the Lab color space, as shown in formula (4):

[0082] Δ C x - d , y g ( i , j ) = Σ c ∈ { Lab } ( g c ( x - d + i , y + ...

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Abstract

The invention discloses a parallax estimation method based on improved adaptive weighted summation and confidence propagation, belonging to the computer stereo visual sense technology field. The invention solves the problems that matching accuracy of the parallax calculated by the current matching algorithm in the shielding area and depth discontinuous area is low, that the high accuracy matching algorithm has heavy calculation quantity, that the implementation is poor, and the refinement method parallax plane estimation based on the segmentation is not accurate. The parallax estimation method comprises steps of computing correlated values among matching pixels by utilizing the weight class changing method, performing matching on shielding pixels afresh through improving the adaptive weight method, using the improved confidence propagation algorithm to perform global optimization on a disparity map, using a refinement module to perform refinement on the disparity map, and utilizing the improved confidence propagation algorithm again and the correlated value and the disparity map to perform global optimization. The invention can be applied in segmentation of the stereo image, encoding of the stereo video, robot vision, target tracking, etc.

Description

technical field [0001] The invention relates to a parallax estimation method, in particular to a parallax estimation method based on improved adaptive weighting and confidence propagation, and belongs to the technical field of computer stereo vision. Background technique [0002] Parallax evaluation is the basis of computer stereo vision. In recent years, with the improvement of computer performance, parallax evaluation has attracted more and more attention. It has broad application prospects in military, aviation, robot navigation and other fields. The existing disparity estimation algorithms can be divided into two categories: local algorithms and global algorithms. Generally speaking, the calculation speed of the local algorithm is fast, but the calculation accuracy of the disparity is low, while the calculation accuracy of the global algorithm is high, but the complexity of the algorithm is large, and it is difficult to implement. Through the search of the prior art doc...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00
Inventor 荣宪伟薛远洋于晓艳
Owner HARBIN NORMAL UNIVERSITY
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