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A stereo matching, weak texture technology, applied in the field of computer vision, can solve the problems of weak texture area matching difficulties, uneven lighting and overexposure, etc.
Inactive Publication Date: 2017-11-24
HARBIN UNIV OF SCI & TECH
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Problems solved by technology
At present, the problems of stereo matching mainly include external factors such as uneven illumination and overexposure, as well as the characteristics of the image itself that are difficult for computers to distinguish, such as occlusion, weak texture, and repeated texture.
Although a large number of scholars have studied stereo matching for many years, the matching of weak texture areas is still a difficult point in the field of image processing.
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specific Embodiment 1
[0052] A cross-scale cost aggregation stereo matching method based on weak texture detection, such as figure 1 shown, including the following steps:
[0053] Step a, input two color images, described two color images are left image and right image respectively, utilize the gradient information of left image to carry out weak texture detection and segmentation to picture;
[0054] Step b, calculating the matching cost according to the color information and gradient information of the left image and the right image;
[0055] Step c, based on the weak texture detection and segmentation results in step a, perform Gaussian filter-based intra-scale and cross-scale cost aggregation;
[0056] Step d, using the winner-take-all strategy to calculate the disparity;
[0057] In step e, the parallax is refined by using left-right consistency detection and an adaptive weight-based method, and a parallax image is output.
[0058] According to the above steps, select four pictures for comp...
specific Embodiment 2
[0070] In the described method of cross-scale cost aggregation stereo matching based on weak texture detection, the weak texture detection and segmentation of the picture in the step a are specifically as follows:
[0071] Calculate the gradient value of the pixel at the left image coordinates (x, y) g(x, y), and compare it with the gradient threshold g T Compare and judge whether it is a weak texture area, the calculation formula is:
[0072] g(x,y)T
[0073]
[0074] In the formula: N(x, y) represents the window centered on the pixel (x, y), M represents the number of pixels in the window, and I(x, y) represents the gray value of the pixel.
[0075] In the described method of stereo matching based on cross-scale cost aggregation based on weak texture detection, the calculation of the matching cost in the step b is specifically:
[0076] Compute the stereo color image pair left image I L and right image I R The matching cost C(p,d), whose calculation formula is:
[00...
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Abstract
A weak texture detection-based cross-scale cost aggregation stereo matching method of the present invention belongs to the computer vision field, in particular relates to a stereo matching method of the weak texture images, and comprises the following steps of inputting two color images which are separately a left image and a right image, utilizing the gradient information of the left image to carry out the weak texture detection and segmentation on a picture; calculating the matching cost according to the gradient information and the color information of the left image and the right image; taking the above weak texture detection and segmentation results as the references to carry out the Gaussian filter-based internal scale and cross-scale cost aggregation; adopting a winner taking strategy to calculate the parallax; adopting the left and right consistency detection and an adaptive weight-based method to refine the parallax, and outputting a parallax image. The method of the present invention achieves the technical purposes of improving the weak texture area matching correct rate under the premise of guaranteeing the texture area matching correct rate, and obtaining the better parallax image.
Description
technical field [0001] A cross-scale cost aggregation stereo matching method based on weak texture detection in the present invention belongs to the field of computer vision, and in particular relates to a stereo matching method for weak texture images. Background technique [0002] Binocular stereo vision (Binocular Stereo Vision) is an important form of computer vision. It is based on the principle of parallax and uses imaging equipment to obtain two images of the measured object from different positions. By calculating the position deviation between the corresponding points of the image, to obtain A method for 3D geometric information of an object. The quality of 3D information acquisition mainly depends on the accuracy of the disparity map obtained by stereo matching. At present, the problems of stereo matching mainly include external factors such as uneven illumination and overexposure, as well as the characteristics of the picture itself that are difficult for compute...
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