Method for acquiring range image by stereo matching of multi-aperture photographing based on color segmentation

Abstract

The invention discloses a method for acquiring a range image by stereo matching of multi-aperture photographing based on color segmentation. The method comprises the following steps of: (1) carrying out image correction on all input images; (2) carrying out the color segmentation on a reference image, and extracting an area with consistent color in the reference image; (3) respectively carrying out local window matching on the multiple input images to obtain multiple parallax images; (4) removing mismatched points which are generated during the matching by applying a bilateral matching strategy; (5) synthesizing the multiple parallax images into a parallax image, and filling parallax information of the mismatched points; (6) carrying out post-treatment optimization on the parallax image to obtain a dense parallax image; and (7) converting the parallax image into a range image according to the relationship between parallax and depth. By acquiring range information from multiple viewpoint images and utilizing image information provided by the multiple viewpoint images, the invention can not only solve the problem of mismatching brought by periodic repetitive textural features and shelter and the like in the images, but also can improve matching precision and obtain an accurate range image.

Description

Technical field [0001] The invention relates to a method for acquiring a depth image, in particular to a method for acquiring a depth image by multi-eye camera stereo matching based on color segmentation. Background technique [0002] Depth Image Based Rendering (DIBR) technology is a key technology on the decoding side of the 3DTV system. DIBR technology uses color images and their corresponding depth images to generate new viewpoint images by introducing depth information to visible pixels in the source image. Due to the huge amount of data that needs to be transmitted for compressing and transmitting multi-channel video, the required bandwidth will increase significantly. Especially if users are allowed to select viewpoints, a dense camera array is required for collection, which makes the amount of multi-viewpoint video data increase sharply , Which seriously hinders the application of 3DTV. Therefore, the representation method of "single-view video + depth" is used as an al...

AI Technical Summary

Problems solved by technology

The stereo matching algorithm based on the region (window) can easily restore the parallax in the high texture region, but it will cause a large number of mismatches in the low texture region, resulting in blurred boundaries, and it is also difficult to process the occluded region; The feature points extracted by the feature-based stereo matching method are not too sensitive to noise, so more accurate matching can be obtained, but because the feature points in the image are very sparse, this method can only obtain a sparse disparity map

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