Fast and Robust Random-Valued Image Denoising Algorithm based on Road Statistics
In this paper, an efficient, low computational complexity, and threshold free random-valued impulse noise removal
is proposed. Based on a well-known Rank-Ordered Absolute Difference (ROAD), a four-state filter is proposed to detect and
recover corrupted pixels. The minimum, maximum, sum and median ROAD are used as parameters for classifying impulse
noise which eliminate the need for threshold value. The experimental results demonstrate the efficiency of the proposed
algorithm in dealing with images corrupted by high random-valued and fixed-valued impulse noise as compared with two
state-of-the-art denoising algorithms.
Index Terms - Image denoising, Random-valued impulse noise, Fixed-valued impulse noise, Impulse detector.