A Stereo Matching with Reconstruction Network for Low-light Stereo Vision

Abstract

To solve the problem existing in the stereo matching of low-light images, this paper proposes a stereo matching with reconstruction network based on pyramid stereo matching network(PSMNet) and reconstruction module. In view of the characteristics of the low-light image with severe and complex noise, the image reconstruction module is added into the traditional stereo matching network for automatic denoising. In this process, the image reconstruction module assists the stereo matching module in model training, so as to reduce the influence of noise on stereo matching and obtain more accurate results. The proposed method has been evaluated and achieves good performance on the Middlebury dataset which is preprocessed. In addition, a low-light binocular platform is built to get the true low-light image and test our network in night environment, results show the disparity maps are more accurate compared with previous methods.