光学学报, 2017, 37 (11): 1110001, 网络出版: 2018-09-07   

基于非局部先验的单幅图像去雾算法 下载: 1213次

Single Image Dehazing Algorithm Based On Non-Local Prior
作者单位
空军工程大学航空航天工程学院, 陕西 西安 710038
摘要
现有单幅图像去雾算法大多基于局部先验,去雾结果存在块效应。在处理浓雾区域时,如果没有特殊处理,会导致图像中的一些伪影被增大,比如在原始的有雾图像中几乎不可见的噪声、色彩重叠等,在去雾后的图像中被增强,进而影响图像质量。针对以上存在的问题,提出了一种改进算法。首先采用非局部先验,估算初始的透射率,然后采用正则化的方法优化透射率,并且将原始图像和去雾后图像的梯度差L1/2范数作为正则化项,达到抑制噪声干扰的目的。结果表明,该算法能够很好地恢复出图像的细节信息和色彩;与局部先验方法相比,具有更好的稳健性。
Abstract
Most of the existing single image dehazing algorithms are on the basis of local priors, and there is block effect in dehazing results. The image artifacts are augmented at heavy haze regions, if there is no special treatment. For example, the noise and color overlap which are almost invisible in the original haze image are enhanced after dehazing, and affect the quality of the dehazing images. In order to eliminate these disadvantages, a novel image dehazing algorithm is proposed. Firstly, the non-local prior is adopted to estimate the initial transmission. Then, a regularized method is used to optimize it, the L1/2 norm of gradient difference of original image and dehazing image is used as regularization term to suppress the noise interference. The results show that the proposed algorithm can recover the details and color effectively, and has better robustness than the local prior methods.

董亚运, 毕笃彦, 何林远, 马时平. 基于非局部先验的单幅图像去雾算法[J]. 光学学报, 2017, 37(11): 1110001. Yayun Dong, Duyan Bi, Linyuan He, Shiping Ma. Single Image Dehazing Algorithm Based On Non-Local Prior[J]. Acta Optica Sinica, 2017, 37(11): 1110001.

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