Fast Image Restoration for Spatially Varying Defocus Blur of Imaging Sensor

Sensors

Hejin Cheong¹  Eunjung Chae¹  Eunsung Lee¹  Gwanghyun Jo¹ 

[1] Department of Image, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 156-756, Korea;

关键词: image restoration;    spatially varying blur;    truncated constraint least-squares (TCLS) filter;    point spread function estimation;   

DOI  :  10.3390/s150100880

来源: mdpi

【 摘 要 】

This paper presents a fast adaptive image restoration method for removing spatially varying out-of-focus blur of a general imaging sensor. After estimating the parameters of space-variant point-spread-function (PSF) using the derivative in each uniformly blurred region, the proposed method performs spatially adaptive image restoration by selecting the optimal restoration filter according to the estimated blur parameters. Each restoration filter is implemented in the form of a combination of multiple FIR filters, which guarantees the fast image restoration without the need of iterative or recursive processing. Experimental results show that the proposed method outperforms existing space-invariant restoration methods in the sense of both objective and subjective performance measures. The proposed algorithm can be employed to a wide area of image restoration applications, such as mobile imaging devices, robot vision, and satellite image processing.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.