Inter-color correlation-based stereo matching sparse block aggregation strategy method

A stereo matching and color technology, applied in the field of computer vision, can solve the problems of increased parallax value error, large algorithm calculation amount, blurred boundary, etc., to achieve the effect of improving accuracy, reducing calculation amount, and increasing representation

Inactive Publication Date: 2018-11-06
CHANGCHUN UNIV OF SCI & TECH
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Problems solved by technology

Hu W defines a virtual support window for a pixel in the matching cost aggregation, which can select the most relevant pixel, effectively avoiding the mismatch caused by the uncertainty of image correspondence, but the amount of calculation is still large
[0004] In the existing stereo matching process, when the size of the matching window is smaller, the stereo matching accuracy in the strong texture area of ​​the image is higher, but due to the lack of sufficient information, the parallax value error in the single texture area will increase
Conversely, when the size of the matching window is larger, the interference of image noise can be eliminated more effectively, but because it contains more information, it will lead to blurred boundaries at discontinuous areas of parallax, and the calculation of the algorithm is larger

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  • Inter-color correlation-based stereo matching sparse block aggregation strategy method
  • Inter-color correlation-based stereo matching sparse block aggregation strategy method
  • Inter-color correlation-based stereo matching sparse block aggregation strategy method

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Embodiment Construction

[0054] The present invention will be further described below in conjunction with the accompanying drawings: figure 1 As shown, based on the three-dimensional matching sparse block aggregation strategy method based on correlation within the color, the device is a computer 1; it is characterized in that the specific steps are as follows:

[0055] Step 1. Computer 1 logs on to the vision.middlebury.edu website and obtains a standard Teddy image pair from it. The left and right image sizes used in the left image LeftImg and the right image RightImg are both NX×NY=450pixel×375pixel.

[0056] Step 2. In the left image LeftImg, using the leftmost side of each row as the starting point, construct a W×W rectangular support window, W=39. The center pixel of the window is the point to be matched p, set the coordinates of the current point to be matched to (x,y), x=1, 2,...,NX,y=1, 2,...,NY (NX=450, NY=375 ). The RGB values ​​of pixel p are respectively p R , P G , P B Said. The other pixe...

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Abstract

The invention relates to an inter-color correlation-based stereo matching sparse block aggregation strategy method. The method is characterized by comprising the following steps of: obtaining a groupof test images from a Middlebury data set platform and transmitting the test images into a computer 1; improving a matching cost function by utilizing correlation between a pixel and a color space soas to better express local properties of the pixel; constructing a mean value block-based sparse aggregation strategy to improve the algorithm efficiency; and eliminating mis-matched points by utilizing left-right consistency detection and median filter. Through the method, the matching precision in weak texture areas is improved and the operation time is shortened.

Description

Technical field [0001] The invention relates to a three-dimensional matching sparse block aggregation strategy method based on color correlation, and belongs to the technical field of computer vision. Background technique [0002] Stereo matching is one of the most active research topics in the field of computer vision, and it has a wide range of applications in three-dimensional reconstruction, unmanned driving, virtual reality and other fields. Its purpose is to find the corresponding pixel point of each pixel in another image from a given pair of left and right images. The difference between the positions of two matching pixels is called parallax. [0003] The current mainstream local stereo matching algorithms are divided into adaptive window algorithm and adaptive weight algorithm. The adaptive window algorithm uses different window sizes for different pixels according to the local attributes of the pixels. In contrast, the adaptive weighting algorithm adjusts the weights of...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/593G06T7/90
CPCG06T2207/10012G06T2207/10024G06T2207/20032G06T7/593G06T7/90
Inventor 韩成杨帆张超丁莹权巍姜珊金龙斌刘文
Owner CHANGCHUN UNIV OF SCI & TECH
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