Hybrid Filter Based on Fuzzy Techniques for Mixed Noise Reduction in Color Images

被引:17
作者
Arnal, Josep [1 ]
Sucar, Luis [1 ]
机构
[1] Univ Alicante, Dept Comp Sci & Artificial Intelligence, Campus St Vicent del Raspeig S-N, St Vicent Del Raspeig 03690, Spain
来源
APPLIED SCIENCES-BASEL | 2020年 / 10卷 / 01期
关键词
image enhancement; noise filtering; mixed Gaussian and impulsive noise; fuzzy logic; IMPULSIVE NOISE; PEER GROUP; REMOVAL ALGORITHM; BILATERAL FILTER;
D O I
10.3390/app10010243
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
To decrease contamination from a mixed combination of impulse and Gaussian noise on color digital images, a novel hybrid filter is proposed. The new technique is composed of two stages. A filter based on a fuzzy metric is used for the reduction of impulse noise at the first stage. At the second stage, to remove Gaussian noise, a fuzzy peer group method is applied on the image generated from the previous stage. The performance of the introduced algorithm was evaluated on standard test images employing widely used objective quality metrics. The new approach can efficiently reduce both impulse and Gaussian noise, as much as mixed noise. The proposed filtering method was compared to the state-of-the-art methodologies: adaptive nearest neighbor filter, alternating projections filter, color block-matching 3D filter, fuzzy peer group averaging filter, partition-based trimmed vector median filter, trilateral filter, fuzzy wavelet shrinkage denoising filter, graph regularization filter, iterative peer group switching vector filter, peer group method, and the fuzzy vector median method. The experiments demonstrated that the introduced noise reduction technique outperforms those state-of-the-art filters with respect to the metrics peak signal to noise ratio (PSNR), the mean absolute error (MAE), and the normalized color difference (NCD).
引用
收藏
页数:17
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