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Graph cut stereo matching method based on adaptive weight

An adaptive weight and stereo matching technology, which is applied in image enhancement, image analysis, image data processing, etc., can solve the problems of low matching accuracy and high computational complexity of traditional graph cuts

Inactive Publication Date: 2018-09-07
KUNMING UNIV OF SCI & TECH
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Problems solved by technology

[0003] Aiming at the problems of high computational complexity and low accuracy of traditional graph-cut matching in traditional adaptive weights, the present invention provides a graph-cut stereo matching method based on adaptive weights

Method used

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  • Graph cut stereo matching method based on adaptive weight
  • Graph cut stereo matching method based on adaptive weight
  • Graph cut stereo matching method based on adaptive weight

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Experimental program
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Embodiment 1

[0044] Embodiment 1: as Figure 1-4 As shown, a graph-cut stereo matching method based on adaptive weights, the specific steps of the method are as follows:

[0045] Step 1: Open the left and right image pair for testing (the left and right images are captured by the photos installed on the left and right sides), the left image is marked as the reference image, and the right image is marked as the target image.

[0046] Step 2: Data item calculation, the specific implementation method is as follows:

[0047] The expression of each pixel weight in the matching window can be written as:

[0048] w(p,q)=f g (Δg pq ) f s (Δs pq ) (1)

[0049] Among them, fg(Δg pq ) and fs(Δs pq ) respectively represent the gray-scale weight and spatial weight of the central pixel p and the neighborhood pixel q in the matching window of the reference image;

[0050] According to the gray similarity principle, the function fg(Δg pq ) definition, with the absolute value Δ of the pixel p and...

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Abstract

The invention relates to a graph cut stereo matching method based on adaptive weight, and belongs to the neighborhood of binocular stereoscopic vision technology. The method comprises firstly redefining the data items of an energy function according to grayscale similarity and spatial similarity under the theoretical framework of the adaptive weight, and using the gradient information of an imageas the smooth item of the energy function; then solving a model by using a graph cut theory and an [alpha] extended algorithm; and finally, subjecting a disparity map to disparity refinement by usingleft and right consistency test and weighted median filtering to obtain a high-precision disparity map. Four international standard stereo image pairs provided by the Middlebury website are used for testing and experiments show that the method can obtain a more accurate disparity map.

Description

technical field [0001] The invention relates to a graph-cut stereo matching method based on self-adaptive weight, which belongs to the technical field of binocular stereo vision. Background technique [0002] The essence of stereo matching is to search for the positions of points in different views after imaging in the space, and thus obtain the corresponding disparity images. Generally speaking, stereo matching algorithms can be divided into local matching algorithms and global matching algorithms. The local stereo matching algorithm uses a local optimization method for disparity estimation. The main algorithms include SAD, SSD, NCC, and ZNCC. The energy function generally only has data items and no smoothing items. The local algorithm has small memory footprint, fast algorithm speed, and can meet real-time However, there are often high mismatches in occlusion, no texture and repeated texture areas, and the overall matching accuracy is not high. Kanade and Okutomi select ...

Claims

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Application Information

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IPC IPC(8): G06T7/30G06T7/11G06T7/40G06T5/40G06T5/00
CPCG06T5/40G06T7/11G06T7/30G06T7/40G06T2207/20032G06T5/70
Inventor 李文国陈田
Owner KUNMING UNIV OF SCI & TECH
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