Most image processing applications require noise elimination. For example, in applications where derivative operators are applied, any noise in the image can result in serious errors. Impulsive noise appears as a sprinkle of dark and bright spots. Transmission errors, corrupted pixel elements in the camera sensors, or faulty memory locations can cause impulsive noise. Linear filters fail to sup...

This paper presents a spatially-varying speckle noise removal method that does not require any noise parameters or image reconstruction factors to be predetermined by the user. It automatically estimates local noise variances by solving an optimization problem that is based on the scale invariant property of ’kurtosis’ for radar imagery. Then, it aggregates multiple estimations at each pixel us...

The documents may contain noise at the time of scanning, transmission or during converting into it in digital form. be categorized after finding features and find same patterns document image order to obtain accurate method for their elimination. removal from is an important phase development high-quality Optical Character Recognition (OCR) system. To make this possible, paper presents a robust...