Neural network adaptive switching median filter for the restoration of impulse noise corrupted images

Authors:
Pavel S. Zvonarev;Ilia V. Apalkov;Vladimir V. Khryashchev;Irina V. Reznikova
Affiliations:
Digital Circuits and Signals Laboratory, Department of Physics, Yaroslavl State University, Yaroslavl, Russia;Digital Circuits and Signals Laboratory, Department of Physics, Yaroslavl State University, Yaroslavl, Russia;Digital Circuits and Signals Laboratory, Department of Physics, Yaroslavl State University, Yaroslavl, Russia;Digital Circuits and Signals Laboratory, Department of Physics, Yaroslavl State University, Yaroslavl, Russia
Venue:
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
Year:
2005

Citing 4
Cited 0

Detail-preserving median based filters in image processing

Pattern Recognition Letters
A neural network adaptive filter for the removal of impulse noise in digital images

Neural Networks
Nonlinear image processing

Nonlinear image processing
Adaptive median filters: new algorithms and results

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

A new neural network adaptive switching median (NASM) filter is proposed to remove salt-and-pepper impulse noise from corrupted image. The algorithm is developed by combining advantages of the known median-type filters with impulse detection scheme and the neural network was included into impulse detection step to improve its characteristics. Comparison of the given method with traditional filters is provided. A visual example is given to demonstrate the performance of the proposed filter.