Modified Depth-Map Inpainting Method Using the Neural Network

• Main Authors: Gapon Nikolay, Sizyakin Roman, Zhdanova Marina, Balabaeva Oksana, Cen Yigang
• Format: Article
• Language: English
• Published: EDP Sciences 2019-01-01
• Series: EPJ Web of Conferences
• Online Access: https://www.epj-conferences.org/articles/epjconf/pdf/2019/29/epjconf_mnps2018_04005.pdf

This paper proposes a method for reconstructing a depth map obtained using a stereo pair image. The proposed approach is based on a geometric model for the synthesis of patches. The entire image is preliminarily divided into blocks of different size, where large blocks are used to restore homogeneous areas, and small blocks are used to restore details of the image structure. Lost pixels are recovered by copying the pixel values from the source based on the similarity criterion. We used a trained neural network to select the “best like” patch. Experimental results show that the proposed method gives better results than other modern methods, both in subjective and objective measurements for reconstructing a depth map.