An Adaptive Median Filter Based on the Double Windows and Extremum-compressing
To remove mixed impulse noise and Gauss noise in digital images,a new mixed filter based on the adaptive median filter and fuzzy weighted mean filter is proposed.
Impulse noise reduction by variational method based on adaptive median filter
To improve the performance of impulse noise reduction,a new variational method based on adaptive median filter was proposed.
To improve the performances of median filter and enhance the adaptability for the diverse density pepper and salt noises an adaptive median filter,based on the double windows and extremum-compressing filtering(DWECAMF),is proposed for images corrupted with pepper and salt noises. The filter is improved from the standard median filter on the three standpoints: accurateness of noise detection,validity of noise removal and practicability of filtering speed.
Self-adapting Median Filtering Under Muti-window Structures in the Digital Image Processing
Third,variational method was used to get the optimal solution which minimize the cost function and restore the noisy pixels.
And a novel algorithm is provided that adopts local contrast enhancement algorithm based on the nonlinear characteristic of eye vision response following median filter.
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The adaptive median filter is based on transconductance comparators, whose saturation current is adapted to act as a local weight operator.
A 249 × 209 pixel image, corrupted with 35% salt and pepper noise, is used to test the adaptive median filter.
Suppression of Impulse Noise in Medical Images with the Use of Fuzzy Adaptive Median Filter
The RBFAM filter is an improved version of Adaptive Median Filter (AMF) and is presented in the aim of noise reduction of images corrupted with additive impulse noise.
Two of those stages are fuzzy rule based and last stage is based on standard median and adaptive median filter.