Geometric features-based filtering for suppression of impulse noise in color images.
A geometric features-based filtering technique, named as the adaptive geometric features based filtering technique (AGFF), is presented for removal of impulse noise in corrupted color images. In contrast with the traditional noise detection techniques where only 1-D statistical information is used for noise detection and estimation, a novel noise detection method is proposed based on geometric characteristics and features (i.e., the 2-D information) of the corrupted pixel or the pixel region, leading to effective and efficient noise detection and estimation outcomes. A progressive restoration mechanism is devised using multipass nonlinear operations which adapt to the intensity and the types of the noise. Extensive experiments conducted using a wide range of test color images have shown that the AGFF is superior to a number of existing well-known benchmark techniques, in terms of standard image restoration performance criteria, including objective measurements, the visual image quality, and the computational complexity.
Xu
Zhengya
Z
School of Electrical and Computer Engineering, Royal Melbourne Institute of Technology, Melbourne, Victoria 3001, Australia. zhengya.xu@rmit.edu.au
Wu
Hong Ren
HR
Qiu
Bin
B
Yu
Xinghuo
X