There exists spectral gap between visible (VIS) and near infrared (NIR) images causing dissimilar intensity according to reflection property of objects and materials. Therefore, it has a limit of applying traditional stereo matching to cross spectral disparity estimation. In this paper, we propose cross spectral disparity estimation from VIS and NIR paired images using disentangled representation and reversible neural networks. We build a supervised learning framework based on reversible blocks to extract scene features robust against the spectral gap. Reversible blocks decompose features into scene and style components to bridge the spectral gap between VIS and NIR images. We perform stereo matching on the scene component to get an initial disparity map by a 3D convolutional neural network. To generate clear edges in the disparity map, we use a semantic segmentation network as auxiliary information to refine the initial disparity map. Besides, to consider the lack of the ground truth, we synthesize reference disparity maps with guided image filtering. Experimental results demonstrate that the proposed method achieves accurate edges in disparity along object boundaries and outperforms the state-of-the-art methods in both visual comparison and quantitative measurements.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Cross Spectral Disparity Estimation From VIS and NIR Paired Images Using Disentangled Representation and Reversible Neural Networks


    Contributors:
    Han, Qihui (author) / Jung, Cheolkon (author)


    Publication date :

    2023-05-01


    Size :

    1883271 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Motion Estimation from Disparity Images

    Demirdjian, D. / Darrell, T. / IEEE | British Library Conference Proceedings | 2001


    Motion estimation from disparity images

    Demirdjian, D. / Darrell, T. | IEEE | 2001


    Enhanced disparity estimation in stereo images

    Kordelas, G. A. / Alexiadis, D. S. / Daras, P. et al. | British Library Online Contents | 2015


    Vehicle Detection and Disparity Estimation Using Blended Stereo Images

    Zhou, Changxin / Liu, Yazhou / Sun, Quansen et al. | IEEE | 2021


    Disparity Estimation Using Stereo Images With Different Focal Lengths

    Dinh, Vinh Quang / Munir, Farzeen / Sheri, Ahmad Muqeem et al. | IEEE | 2020