光子学报, 2018, 47 (10): 1010002, 网络出版: 2018-12-18
多局部模糊核融合的图像盲去模糊算法
Blind Image Deblurring via Multi-local Kernels′ Fusion
图像复原 图像增强 盲去模糊 暗通道 局部模糊核融合 点扩散函数 关联性调整 Image restoration Image enhancement Blind deconvolution Dark-channel Local kernels′ fusion Point spread function Relevance adjustment
摘要
针对暗通道先验时间复杂度高的问题, 提出一种多局部模糊核融合的盲去模糊算法.该算法采用并行方式分块求解局部模糊核, 利用局部模糊核的形状相似性将其融合为一个全局模糊核(点扩散函数).对于初步融合的全局模糊核上出现的噪点, 利用其邻域的情况进行关联性调整, 进一步改善融合效果.实验和统计分析结果表明, 该算法在保证去模糊效果的情况下, 有效提升了图像去模糊的速度, 在部分真实模糊图像的局部细节还原上效果更佳, 并且可以很好地处理大尺寸的模糊图像.
Abstract
A multi-local kernels′ fusion algorithm is proposed to solve the problem of high complexity of dark channel priors. In this algorithm, the local kernels are computed and solved in parallel, and then merged into a global kernel (point spread function) by using the shape similarity of local kernels. For the noise that has appeared on the initially merged global kernel, the relevance adjustment is introduced using the neighboring information to further improve the fusion effect. Experiments show that the proposed algorithm can effectively improve the speed of image deblurring while guaranteeing the deblurring effect. It also has better effect on the local detail restoration of some real blurred images, and can handle large-size blurred images well.
陈春雷, 叶东毅, 陈昭炯. 多局部模糊核融合的图像盲去模糊算法[J]. 光子学报, 2018, 47(10): 1010002. CHEN Chun-lei, YE Dong-yi, CHEN Zhao-jiong. Blind Image Deblurring via Multi-local Kernels′ Fusion[J]. ACTA PHOTONICA SINICA, 2018, 47(10): 1010002.