Local three-dimensional matching method based on credible point spreading

A stereo matching and credible point technology, which is applied in image data processing, instrumentation, calculation, etc., can solve the problems of poor matching cost calculation accuracy, many large steps, etc., to achieve reasonable determination, guaranteed accuracy, and reduced data volume. Effect

Active Publication Date: 2013-03-27
SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
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Problems solved by technology

[0006] In order to solve the problems in the prior art that the processing of occlusion points and untrustworthy points has a large amount of...

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  • Local three-dimensional matching method based on credible point spreading
  • Local three-dimensional matching method based on credible point spreading
  • Local three-dimensional matching method based on credible point spreading

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Embodiment Construction

[0038] The present invention uses the improved AD-cencus algorithm to calculate the initial disparity by processing the DSCI image, and introduces the gradient information in the conversion window, so that the component weights of the AD calculation and the cencus conversion can be adjusted according to the gradient information, so that the AD-cencus The algorithm is more flexible, and the more situations it can solve, the better the algorithm. Regarding the DSCI diagram, give an example as follows. Take the DSCI picture on the left as an example. The meaning is that for each point in the left picture, you need to find a matching point in the right picture. If you know its matching point in the right picture, you can directly calculate the disparity value. When searching for matching points, the present invention first assumes a disparity range. Under different disparity value assumptions, a point in the right picture can be found (uniquely determined by this hypothetical dispa...

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Abstract

The invention discloses a local three-dimensional matching method based on credible point spreading. The local three-dimensional matching method includes: a, at least calculating minimum values and second minimum values of matching cost of pixel points under different parallax hypothesis by utilizing an AD (absolute intensity differences)-Census algorithm, and obtaining a DSCI image by combining with gradient information of images; b, obtaining initial disparity maps of the images according to the DSCI; c, dividing the pixel points into credible points, unlikelihood points and shielding points, wherein the credible points are determined by combining with the minimum values and the second minimum values to the matching cost; d, calculating the disparity values of the credible points and processing the unlikelihood points and the shielding points through the credible points to obtain the disparity values; and e, outputting a disparity image. The local three-dimensional matching method based on the credible point spreading effectively utilizes data in an initial disparity image, enables the credible points to be determined reasonably and accurately, further enables the following processing on the unlikelihood points and the shielding points to be accurate and finally ensures the accuracy of the matching method.

Description

Technical field [0001] The invention relates to the field of image data processing, in particular to a local stereo matching method based on credible point propagation. Background technique [0002] Stereo matching technology refers to pictures taken from different viewpoints of the same scene to find the correspondence between their pixels. This corresponding relationship is represented by a disparity map, which contains the depth information of the pixels in the image. [0003] Currently, binocular stereo matching methods based on dense disparity maps are mainly divided into two categories, one is the local stereo matching method, and the corresponding is the global stereo matching method. [0004] AD-Census is a local stereo matching method. AD (absolute intensity differences) represents the absolute value of the gray difference of the matched pair, and Census represents the Census transform. This conversion characterizes the structural characteristics around the pixel. Compar...

Claims

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Application Information

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IPC IPC(8): G06T7/00
Inventor 王好谦吴勉戴琼海
Owner SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
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