期刊论文

Zhao, Hui-Huang

英文

Multimedia Tools and Applications

1380-7501

2020

79

21-22

14825-14847

10.1007/s11042-019-7647-8

This work was supported by National Natural Science Foundation of China (61503128), Science and Technology Plan Project of Hunan Province (2016TP1020), Scientific Research Fund of Hunan Provincial Education Department (16C0226,17C0223,18A333), Hengyang guided science and technology projects and Application-oriented Special Disciplines (Hengkefa [2018]60-31), Double First-Class University Project of Hunan Province (Xiangjiaotong [2018]469), Hunan Province Special Funds of Central Government for Guiding Local Science and Technology Development (2018CT5001) and Subject Group Construction Project of Hengyang Normal University (18XKQ02). We would like to thank NVIDIA for the GPU donation.

本校为通讯机构

This paper develops a novel adaptive gradient-based block compressive sensing (AGbBCS_SP) methodology for noisy image compression and reconstruction. The AGbBCS_SP approach splits an image into blocks by maximizing their sparsity, and reconstructs images by solving a convex optimization problem. In block compressive sensing, the commonly used square block shapes cannot always produce the best results. The main contribution of our paper is to provide an adaptive method for block shape selection, improving noisy image reconstruction performance. The proposed algorithm can adaptively achieve bett...