Adaptive Iteration Filter for Suppression of Impulse Noise in Color Images

Abstract

New impulse detection and filtering algorithm is proposed in color images. Based on fast peer group filter, the proposed filtering algorithm uses different iteration times to complete filter according to different impulse noise density. The extensive experimental results show that the proposed scheme provides better performance than many of the existing vector filters. Meanwhile, the proposed approach is simple and practical for real-time application.

Fuzzy decision filter for color images denoising

“…If the central pixel of a local window is classified to be noisy, this center pixel is replaced by a weighted median value on an optimum direction, enabling impulse noise to be removed [15]. In paper [16,7,17], an impulse detection scheme is proposed which can effectively detect impulse noise. Filters with switching scheme have a great development.…”

An improved non-local means filter for color image denoising

“…However, these filters are spatially invariant operators that make no distinctions between noisy and noise-free pixels. To avoid damaging clean pixels in color images, adaptive vector median filter (AVMF) [4,5], fast peer group filter (FPGF) [6,7] and vector lower-upper-middle smoother (VLUM) [8] are widely used by certain switching schemes. Moreover, These filters are computationally efficient and perform reasonably well in removing noise.…”