A universal noise removal algorithm with an impulse detector.
We introduce a local image statistic for identifying noise pixels in images corrupted with impulse noise of random values. The statistical values quantify how different in intensity the particular pixels are from their most similar neighbors. We continue to demonstrate how this statistic may be incorporated into a filter designed to remove additive Gaussian noise. The result is a new filter capable of reducing both Gaussian and impulse noises from noisy images effectively, which performs remarkably well, both in terms of quantitative measures of signal restoration and qualitative judgements of image quality. Our approach is extended to automatically remove any mix of Gaussian and impulse noise.
Garnett
Roman
R
Department of Mathematics, Washington University in Saint Louis, MO 63130, USA. roman@math.wustl.edu
Huegerich
Timothy
T
Chui
Charles
C
He
Wenjie
W
D000465:Algorithms; D016477:Artifacts; D001185:Artificial Intelligence; D003198:Computer Simulation; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D015233:Models, Statistical; D009716:Numerical Analysis, Computer-Assisted; D012815:Signal Processing, Computer-Assisted; D013269:Stochastic Processes