平滑的
双边滤波器
核(代数)
杠杆(统计)
图像(数学)
人工智能
边缘保持平滑
计算机科学
数学优化
计算机视觉
图像处理
滤波器(信号处理)
核更平滑
正规化(语言学)
图像复原
数学
算法
核方法
支持向量机
径向基函数核
组合数学
作者
Yang Yang,Yue Sun,Wei Gao,Xinyu Wang,Lanling Zeng
标识
DOI:10.1016/j.imavis.2024.105031
摘要
Edge-preserving image smoothing is vital in the field of image processing and computational photography. The state-of-the-art filters based on optimization models have achieved promising performance. However, most of them fail to consider the spatial support in the regularization term, thus limiting the edge-preserving capabilities. In this paper, inspired by the bilateral filter, which consists of a range kernel and a spatial kernel. we propose to leverage bilateral kernel as a penalty function, and embed it into an optimization model for edge-preserving image smoothing. Furthermore, we propose to incorporate an edge-aware weighted scheme in the data term design, which further improves the edge-preserving capability. The bilateral function is non-convex and can be non-trivial to solve. In this paper, we propose a novel iterative solution based on fixed point iteration, where the main burden in each iteration is a bilateral filtering process. We have conducted extensive experiments to evaluate the proposed filter. Experiment results indicate that our filter benefits a variety of image processing tasks. Moreover, we propose an efficient approximation of the proposed filter, which is able to significantly accelerate the filtering process with neglectable sacrifice of smoothing quality.
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