Title :
Near infrared image de-noise based on lifting wavelets and context model
Author_Institution :
Huangshi Inst. of Technol., Huangshi
Abstract :
According to the characteristic of stochastic noise in near infrared image, and after general consideration about image de-noise smooth effect and image definition, we bring out a method of near infrared image de-noise based on lifting wavelets and context model. Firstly we would lifting wavelets analyze image containing noise, and process soft threshold management on image high frequency part associated with context model, then reconstruct lifting wavelets to get de-noised image. By the evaluation of taking the signal noise ration and image grayness surface diagram as the image de-noising effect, and experiment on the method of image de-noising of lifting wavelets transformation with context model contrast wavelets soft threshold de-noising, the result indicate that it could eliminate image noise and also maintain the requirements of image border, and itpsilas available for near infrared image de-noise.
Keywords :
image denoising; image enhancement; image reconstruction; image segmentation; infrared imaging; smoothing methods; stochastic processes; wavelet transforms; context model; de-noise enhance management; image definition; image grayness surface diagram; lifting wavelet reconstruction; near infrared image de-noise smooth effect; signal noise ration; soft threshold management; stochastic noise; Context modeling; Frequency; Image analysis; Image denoising; Image reconstruction; Infrared imaging; Signal to noise ratio; Stochastic resonance; Surface waves; Wavelet analysis;
Conference_Titel :
Audio, Language and Image Processing, 2008. ICALIP 2008. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-1723-0
Electronic_ISBN :
978-1-4244-1724-7
DOI :
10.1109/ICALIP.2008.4590053
