An adaptive switching filter based on approximated variance for detection of impulse noise from color images

A new adaptive switching algorithm is presented where two adaptive filters are switched correspondingly for lower and higher noise ratio of the image. An adaptive center weighted vector median filter is used for the lower noise ratio whereas for higher noise ratio the noisy pixels are detected based on the comparison of the difference between the mean of the vector pixels in the window and the approximated variance of the vector pixels in the window. Then the window comprising the detected noisy pixel is further considered where the pixels are given exponential weights according to their similarity to the other neighboring pixels, spatially and radio metrically. The noisy pixels are then replaced by the weighted average of the pixels within the window. The filter is able to preserve higher signal content in the higher noise ratio as compared to other robust filters in comparison. With a little high in computational complexity, this technique performs well both in lower and higher noise ratios. Simulation results on various RGB images show that the proposed algorithm outperforms many other existing nonlinear filters in terms of preservation of edges and fine details.