期刊
IEEE SIGNAL PROCESSING LETTERS
卷 27, 期 -, 页码 1670-1674出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LSP.2020.3024990
关键词
Kernel; Image edge detection; Smoothing methods; Filtering; Histograms; Convolution; Noise measurement; Bilateral filter; gaussian range kernel; gaussian spatial kernel; image smoothing
资金
- Ministry of Science and Technology, Taiwan [MOST 108-2221-E-155-034-MY3, MOST 107-2221-E-155-052-MY2]
Recent studies have demonstrated that a bilateral filter can increase the quality of edge-preserving image smoothing significantly. Different strategies or mechanisms have been used to eliminate the brute-force computation in bilateral filters. However, blindly decreasing the processing time of the bilateral filter cannot further ameliorate the effectiveness of filter. In addition, even when the processing speed of the filter is increased, inherent problem occurred in the Gaussian range kernel when facing a noise filtering input and its effect on edge-preserving image smoothing operation are barely discussed. In this letter, we propose a novel Gaussian-adaptive bilateral filter (GABF) to resolve the aforementioned problem. The basic idea is to acquire a low-pass guidance for the range kernel by a Gaussian spatial kernel. Such low-pass guidance lead to a clean Gaussian range kernel for later bilateral composite. The results of experiments conducted on several test datasets indicate that the proposed GABF outperforms most existing bilateral-filter-based methods.
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