Selective removal of impulse noise based on homogeneity level information

By Gouchol Pok, Jyh-Charn S. Liu, Attoor Sanju Nair. IEEE Transactions on Image Processing, 2003

316 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Media Technology, Signal Processing

View Paper: https://www.semanticscholar.org/paper/775a0e7ecccb9ed3c92ff9c3db81c8df27fa9c6c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Yin Zhang
2. Wotao Yin
3. Junfeng Yang
4. Raymond H. Chan
5. Chung-Wa Ho
6. Mila Nikolova
7. Stanley J. Osher
8. Paul Tseng

In Media Technology

1. Raymond H. Chan
2. Yin Zhang
3. Junfeng Yang
4. Chung-Wa Ho
5. Mila Nikolova
6. Wotao Yin

In Signal Processing

1. Wotao Yin
2. Raymond H. Chan
3. Yin Zhang
4. Junfeng Yang
5. Chung-Wa Ho
6. Mila Nikolova
7. Jakub Konecný
8. Taiji Suzuki

Citations in the corpus

• Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization (2005, methodology): “Different remedies of the median filter have been proposed, e.g., the adaptive median filter [5], the multistate median filter [6], or the median filter based on homogeneity information [7], [8].”
• Regularizing Flows for Constrained Matrix-Valued Images (2004, unknown): “Decision-based filters operate over small windows where outliers are first detected and then selectively smoothed [1, 11, 21, 25, 33].”
• An Efficient TVL1 Algorithm for Deblurring Multichannel Images Corrupted by Impulsive Noise (2009, background): “, the adaptive median filter [30], the multistate median filter [18], and the median filter based on homogeneity information [23, 41].”