Depth image fusion method, device and computer-readable storage medium

Abstract

The invention discloses a depth image fusion method, device and computer-readable storage medium. The method includes: acquiring at least one depth image and a reference pixel point in the at least one depth image; A candidate queue corresponding to the reference pixel, where at least one unfused pixel to be fused in the depth image is stored in the candidate queue; a fusion queue corresponding to a reference pixel in the at least one depth image is determined in the candidate queue, And push the pixels to be fused in the candidate queue into the fusion queue, the fusion queue stores at least one selected fusion pixel in the depth image; obtain the feature information of the selected fusion pixels in the fusion queue; according to The feature information of the selected fused pixel points determines the standard feature information of the fused pixel points; according to the standard feature information of the fused pixel points, a fused point cloud corresponding to at least one depth image is generated.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a depth image fusion method, device and computer-readable storage medium. Background technique [0002] With the continuous development of 3D reconstruction technology, more and more 3D reconstruction requirements begin to appear. At present, the main 3D reconstruction methods include: large-scale 3D reconstruction using pictures and multi-view stereo vision technology, 3D reconstruction using lidar scanning scenes, and 3D reconstruction using various structured light scanning devices. One of the core products of all 3D reconstruction is point cloud data. Point cloud data are discrete colored 3D coordinate points. These dense 3D points are combined to describe the entire reconstructed scene. [0003] During the reconstruction process, many parts of the scene will be observed or scanned multiple times, and each observation or scan will generate a lot of point clo...

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Problems solved by technology

[0003] During the reconstruction process, many parts of the scene will be observed or scanned multiple times, and each observation or scan will generate a lot of point clouds describing the part. After the entire reconstruction process, each part of the scene usually has a lot of redundancy points, so that the point cloud of the whole scene is too large, which is not conducive to rendering and display. Moreover, a large number of point clouds generated in this way are often accompanied by more noise

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