Iterative Depth Map Structure Restoration Method Based on RGB-D SSIM Structure Similarity

Abstract

The invention discloses an iterative depth map structure restoration method based on RGB-D SSIM structure similarity. First, the edge of the input depth map is detected, and the edge is expanded, and the expanded area is marked as a potential structural distortion area, and then the Each pixel in the potential structural distortion area judges whether it is distorted, and generates a structural distortion metric index. The distorted pixel uses the product of the Gaussian weight of the color image and the structural distortion metric index to construct a restoration weight, and performs guided restoration through a weighted median filter, and then The distorted area is guided and filtered, and the completed result map continues to iterate according to the above steps until the set termination iteration condition is met, and the depth map is output to end the calculation. The present invention obtains more accurate structural information by iteratively detecting and recovering the structurally distorted area of ​​the depth map, and at the same time denoises and preserves the edges of the structurally undistorted area, finally obtaining a depth map with a clear structure and smooth depth values .

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to an iterative depth map structure restoration method based on RGB-D SSIM structure similarity. Background technique [0002] Depth data plays an important role in the 3D vision system, which can be widely used in various fields such as 3D reconstruction, robot navigation, 3D tracking, unmanned driving, and virtual reality. However, due to the immature depth perception technology at this stage, the depth data obtained by the depth sensor is seriously distorted, so it is necessary to use computational means to repair the depth map data. The acquisition of depth map data is mainly divided into two methods: active and passive. The passive method is to obtain the corresponding depth image by stereo matching the binocular or multi-eye color map. In the past two decades, passive methods have made great progress, but their handling of weak textures and occlusions is ...

AI Technical Summary

Problems solved by technology

However, their recovery of the depth map structure is still poor, and they can only work correctly under the condition that the structure distortion is not serious or even has no structure distortion.

A recently proposed depth image restoration method based on the inconsistent area detection model between the depth image and the RGB image can better restore the structural distortion of the depth image, but it cannot complete the processing and restoration work well when the depth image contains severe structural distortion.

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