Underwater Image Super-Resolution by Descattering and Fusion

IEEE Access

Huimin Lu¹  Seiichi Serikawa¹  Hyongseop Kim¹  Shota Nakashima²  Yujie Li³ 

[1] Kyushu Institute of Technology, Kitakyushu, Japan;Yamaguchi University, Ube, Japan;Yangzhou University, Yangzhou, China;

关键词: Underwater imaging;    descattering;    super resolution;    image fusion;   

DOI  :  10.1109/ACCESS.2017.2648845

来源: DOAJ

【 摘 要 】

Underwater images are degraded due to scatters and absorption, resulting in low contrast and color distortion. In this paper, a novel self-similarity-based method for descattering and super resolution (SR) of underwater images is proposed. The traditional approach of preprocessing the image using a descattering algorithm, followed by application of an SR method, has the limitation that most of the high-frequency information is lost during descattering. Consequently, we propose a novel high turbidity underwater image SR algorithm. We first obtain a high resolution (HR) image of scattered and descattered images by using a self-similarity-based SR algorithm. Next, we apply a convex fusion rule for recovering the final HR image. The super-resolved images have a reasonable noise level after descattering and demonstrate visually more pleasing results than conventional approaches. Furthermore, numerical metrics demonstrate that the proposed algorithm shows a consistent improvement and that edges are significantly enhanced.

【 授权许可】

Unknown