Chinese Optics Letters, Vol. 6, Issue 5, 334 (2008)
Real-time restoration of rotational blurred image using gradient-loading
Chaoyang Han, Jianxun Li*, Xiao Chen, and Zhengfu Zhu
- Department of Automation, Shanghai Jiao Tong University, Shanghai 2002402 Optical Signature of Targets and Environments Key Laboratory of National Defense Science and Technology, Beijing 100854
The key to the restoration of rotational motion blurred image is how to restore the image under a low cost and to correct the irreversibility of the degradation function matrix. Based on the special qualities of degradation function matrix and precise deduction in space-domain, we present a new approach using gradient-loading for restoration of rotational blurred image. By easily adding a gradient operator, the irreversibility of the original matrix is corrected and can be applied for inverse filtering then. Gradient-loading is the optimized approach which combines the advantages of both the approaches using constrained least square filtering and traditional diagonal-loading. Compared with the approach using least square filtering, its peak signal-to-noise ratio (PSNR) is improved from 3.18 to 6.46 dB, while the computing time is reduced to 1/2-1/3. Experimental results demonstrate the effectiveness, noise-resistibility, robustness, and low complexity of this approach, which make it more suitable for real-time environment.