Extending Depth of Field in Noisy Light Field Photography

被引：0

作者：

Tung, Shih-Shuo ^{[1
]}

Shao, Hao-Chiang ^{[2
]}

Hwang, Wen-Liang ^{[1
]}

机构：

[1] Acad Sinica, Inst Informat Sci, Taipei, Taiwan

[2] Ind Technol Res Inst, Computat Intelligence Technol Ctr, Hsinchu, Taiwan

来源：

2017 IEEE 8TH INTERNATIONAL CONFERENCE ON AWARENESS SCIENCE AND TECHNOLOGY (ICAST) | 2017年

关键词：

extending depth of field; light field; image fusion; all-in-focus; CAMERA;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A robust depth of field (DOF) extension algorithm was proposed based on the refocusing property of a light field photograph and the depth-from-defocus approach of multi-focus image fusing. The main techniques of the algorithm are depth estimation and all-in-focus image estimation. By making use of the redundancy of a light field photograph, we leverage both estimations in a noisy environment. For the noise level smaller than 25dB, the proposed algorithm is still robust and the performance is better than other methods both in PSNR and SSIM. We conclude that the algorithm is robust to high noise.

引用

页码：127 / 131

页数：5

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