Adaptive impulse detection using center-weighted median filters

By Tao Chen, Hong Ren Wu. IEEE Signal Processing Letters, 2001

840 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Vision and Pattern Recognition, Signal Processing

View Paper: https://www.semanticscholar.org/paper/8b9f6b9b0e037a95886ae45724f717fb482de0ac

How researchers see this paper

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

In Computational Mechanics

1. Shufang Xu
2. Nor Ashidi Mat Isa
3. Yiqiu Dong
4. Kenny Kal Vin Toh

In Computer Vision and Pattern Recognition

1. Shufang Xu
2. Nor Ashidi Mat Isa
3. Yiqiu Dong
4. Kenny Kal Vin Toh

In Signal Processing

1. Shufang Xu
2. Nor Ashidi Mat Isa
3. Yiqiu Dong
4. Kenny Kal Vin Toh

Citations in the corpus

• Noise Adaptive Fuzzy Switching Median Filter for Salt-and-Pepper Noise Reduction (2010, methodology): “A binary noise mask will be created to mark the location of “noise pixels” by using or otherwise (1) where is the pixel at location with intensity , represents “noise-free pixels” to be retained from the noisy image while represents “noise pixels” subjected to the next filtering stage.”
• Regularizing Flows for Constrained Matrix-Valued Images (2004, neutral): “Decision-based filters operate over small windows where outliers are first detected and then selectively smoothed [1, 11 , 21, 25, 33].”
• A New Directional Weighted Median Filter for Removal of Random-Valued Impulse Noise (2007, methodology): “In order to improve the median filter, many filters with an impulse detector are proposed, such as signal-dependent rank order mean (SD-ROM) filter [7], multistate median (MSM) filter [1], adaptive center weighted median (ACWM) filter [8], the pixelwise MAD (PWMAD) filter [9], and iterative median f”