Title :
The Application of Adaptive Hybrid Filters in Infrared Image Denoising
Author :
Qiao Liyong ; Xu Lixin ; Gao Min ; Zhang Jing ; Yang Yuying
Author_Institution :
Nat. Key Lab. of Mechatron. Eng. & Control, Beijing Inst. of Technol., Beijing, China
Abstract :
Considering the characteristics of infrared images contaminated by Gaussian noise, impulse noise and other mixed noises, an adaptive hybrid filtering algorithm based on infrared image´s local statistical property is presented in this paper. It can automatically detect noises, determine the output based on threshhold value, select the size of filtering window, and judge the image edge on the basis of Laplacian Operator. The experiment results indicate that the presented algorithm has removed the infrared tank image´s mixed noises effectively, preserved the image details and edge features very well, and provided an effective way for infrared image denoising.
Keywords :
Gaussian noise; adaptive optics; image denoising; impulse noise; infrared imaging; optical filters; optical noise; Gaussian noise; Laplacian operator; adaptive hybrid filtering algorithm; automatic noise detection; contaminated infrared images; filtering window; image edge features; impulse noise; infrared image denoising; infrared tank image; local statistical properties; mixed noises; threshhold value; Adaptive filters; Filtering algorithms; Filtering theory; Image edge detection; PSNR;
Conference_Titel :
Photonics and Optoelectronics (SOPO), 2012 Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4577-0909-8
DOI :
10.1109/SOPO.2012.6270910