An Algorithm for Adaptive Mean Filtering and Its Hardware Implementation

Authors:
Ioannis Gasteratos;Antonios Gasteratos;Ioannis Andreadis
Affiliations:
Laboratory of Electronics, Section of Electronics and Information Systems Technology, Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi, Greece GR-67100;Laboratory of Robotics and Automation, Section of Production Systems, Department of Production and Management Engineering, Democritus University of Thrace, Xanthi, Greece GR-67100;Laboratory of Electronics, Section of Electronics and Information Systems Technology, Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi, Greece GR-67100
Venue:
Journal of VLSI Signal Processing Systems
Year:
2006

Citing 6
Cited 1

Digital image processing (2nd ed.)

Digital image processing (2nd ed.)
Machine vision

Machine vision
A Filter To Remove Gaussian Noise by Clustering the Gray Scale

Journal of Mathematical Imaging and Vision
A new gaussian noise filter based on interval type-2 fuzzy logic systems

Soft Computing - A Fusion of Foundations, Methodologies and Applications
Image deblurring in the presence of salt-and-pepper noise

Scale-Space'05 Proceedings of the 5th international conference on Scale Space and PDE Methods in Computer Vision
A new efficient approach for the removal of impulse noise from highly corrupted images

IEEE Transactions on Image Processing

FPGA based disparity map computation with vergence control

Microprocessors & Microsystems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Noise due to the sensor and the electronics of a camera is an undesirable issue in any machine vision application. Such noise tends to corrupt images and to obstruct any further analysis. An algorithm to detect and cancel such noise, using statistical methods, is presented in this paper. The proposed algorithm is an adaptive mean filter, which filters out image regions that are found to be noise corrupted. The efficiency of the proposed filter was examined both qualitatively and quantitatively, by software simulation in several noisy conditions. The main advantage of the filter in hand is that it is appropriate for hardware implementation and can be easily incorporated to smart cameras. The hardware implementation of the filter is also presented in this paper. This implementation aims at time critical applications such as machine vision, inspection and visual surveillance.