High Density Impulse Noise Removal in Color Images Using Region of Interest Median Controlled Adaptive Recursive Weighted Median Filter

An Adaptive varying window size Recursive Weighted Median Filter [ARWMF] for removing the impulse noise in Color images is presented. The weights for the RWMF are calculated by using the median controlled algorithm. By applying Region of Interest [ROI] on selected windows the weight calculation’s efficiency can be increased and the memory will be reduced because of the ROI. In median controlled algorithm, the filter gives the smallest weight for the impulse. However, for many weight functions, including the exponential one, this weight is nonzero. Thus the Impulse has an effect on the output and the magnitude of the impulse is reduced. The window size of the RWMF is adaptive based on the presence of noise density. The performance of the proposed algorithm is given in terms of Mean Square Error (MSE), Mean Absolute Error (MAE) and Peak Signal to Noise Ratio (PSNR) and it is compared with standard median filters, weighted median filters, center weighted median filters, Recursive weighted median filters and Lin’s Adaptive length recursive weighted median filters using median controlled algorithm. Keywords— Adaptive window size, High impulse noise suppression, less computation, Median controlled algorithm, Recursive weighted median filters. Prof. Senthilrajan is with Head Department Master of Computer Application, Jyoti Nivas College, Bangalore, India. IEEE and IAENG Member (e-mail: [email protected]) . Dr.E.Ramaraj is with Director, Computer Department, Alagappa University, Karaikudi, India.