Depth image super-resolution reconstruction based on a modified joint trilateral filter.

ABSTRACT: Depth image super-resolution (SR) is a technique that uses signal processing technology to enhance the resolution of a low-resolution (LR) depth image. Generally, external database or high-resolution (HR) images are needed to acquire prior information for SR reconstruction. To overcome the limitations, a depth image SR method without reference to any external images is proposed. In this paper, a high-quality edge map is first constructed using a sparse coding method, which uses a dictionary learned from the original images at different scales. Then, the high-quality edge map is used to guide the interpolation for depth images by a modified joint trilateral filter. During the interpolation, some information of gradient and structural similarity (SSIM) are added to preserve the detailed info

SUBMITTER: Zhou D 

PROVIDER: S-EPMC6366216 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature