Noise suppression using non-linear PAR model for binary images

The fundamental steps in Digital Image processing are image acquisition, image enhancement, image analysis, image reconstruction, image restoration, image compression, image segmentation, image recognition, and visualization of image. Main sources of noise in digital image processing come under image acquisition, image store and image transmission due to malfunctioning cameras, faulty memory locations and noisy channels respectively. Hence it is necessary to suppress noise in noisy images to extract the necessary details. This paper proposes a method for noise suppression using a parameterized adaptive recursive model for binary images in spatial domain. The type of noise considered is salt and pepper noise. Performance of the proposed method can be measured via subjective results like input-output images and objective like peak signal to noise ratio.