Abstract
Impulse noise is a common noise in digital image processing, which includes the fixed-valued impulse noise and the random-valued impulse noise. A novel method is proposed to detect the fix-value impulse that uses the deviation of slant angle as test object to recognize whether a noise candidate is impulse noise pixel. Distinguishing the average method and medium method, the method uses the new test object to detect the impulse noise. The mathematical model and the detection algorithm of this method are stated and analyzed, and the experiments show the performance of this method under the different circumstance. The biggest advantage of this method is to detect the fixed-valued impulse noise correctly and robustly under the different noise intensity that is up to 0.95.
Highlights
In the digital image processing [1], one of the key problems is the detection and filtering of noise
The main contribution of this paper is to propose a new method to detect the fixed-valued impulse noise
Distinguishing from the traditional average methods and medium methods that are widely studied, this method uses the deviation of slant angle for every pixel candidate as the criterion for noise detection
Summary
In the digital image processing [1], one of the key problems is the detection and filtering of noise. Two noise models are often used to analyze the image noise: additive Gaussian noise and impulse noise. The additive Gaussian noise is defined by adding a value with a zero-mean Gaussian distribution to every original image pixel. Impulse noise is another kind of common noise in digital image, which includes fixed-valued impulse noise and randomvalued impulse noise. A new method is proposed to detect the fixed-valued impulse noise, which is effective to detect heavy polluted image especially. Instead of average detection and medium detection, the deviation of slant angle is chosen as a new test object for the noise detection. We call the new detector as DSA (deviation of slant angle)
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