Removal of random-valued impulse noise by Khalimsky grid

In this paper, based on Khalimsky grid, a new Random-valued Impulse noise identification and removal method is proposed. Khalimsky grid can presents the neighborhood relationship among the pixels in the sliding window, effectively. The local statistics of Khalimsky grid is used to define an adaptive threshold range to identify the central pixel in current sliding window as noisy or noise free in an iterative way. The identified noisy pixel is replaced by local statistics of propose vertical direction based noise removal method. The performance of the propose method is evaluated on different test images and compared with state-of-the-art methods. Experimental results show that the propose method can identify the impulse noise, as well as can preserve the detailed information of an image, efficiently.