New Adaptive Filter For The Removal Of Mixed Noise In Images With Fine Detail Preservation

In this paper, we developed an algorithm to remove additive mixed noise in images with the preservation of fine details and edges. The noise characteristics may vary in the same application from one image to another. In these environments, nonlinear general filters will not perform well and adaptive non-linear filters are best suited. The algorithm based on local statistics such as signal variance and noise Variance is considered. It depends on minimum mean square estimation of the corrupted signal. The signal variance and noise variance are calculated through moving signal window and moving noise window respectively. This offers optimal adaptive filtering in the homogeneous regions as well as in the edges. The fine detail preservation has been obtained by a combining algorithm. The performance of the filters in the presence of different types of noise are evaluated and compared with general mean, bidirectional median filters and median filters. The image enhancement factor has been calculated as the performance-measuring factor. A remotely sensed image has been considered to carryout the subjective and objective analysis of the proposed filter . Key-words:Adaptive max /median, bidirectional median filter, Image enhancement factor, Mean, Median, Nonlinear filter. * Saraswathi Janaki ,Senior Lecturer , Department of ECE, Crescent Engineering College, currently deputed to pursue research in Anna University, Guindy, Chennai,, India.