Optimisation of computer virtual image reconstruction method based on feature point matching

Abstract

Traditional computer virtual image reconstruction methods have the problems of slow reconstruction speed and insufficient image clarity. To solve this problem, an optimisation method of computer virtual image reconstruction based on feature point matching is proposed. SURF operator is used to extract image feature points. After obtaining feature points, image feature points are matched according to TZNCC constraints. The virtual image is reconstructed by sparse method, and the high resolution depth image in virtual vision is represented by dictionary sparse linear combination. The sparse coefficient of the image is solved by alternating direction multiplier algorithm, and the problem of virtual image reconstruction is transformed into a problem of solving sparse signal, so that a better reconstruction effect can be obtained. The experimental results show that the proposed method has high speed and clarity of image reconstruction.