Open AccessImage Restoration Model using Total Variance, Bilateral and Wavelet Denoising Filter
Author(s) -
Mohamed Abdul Kader Jailani N,
V. Thirunavukkarasu
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.c4731.098319
Subject(s) - image restoration , artificial intelligence , computer vision , computer science , noise (video) , filter (signal processing) , wavelet , image (mathematics) , image noise , noise reduction , image processing
Noise in images are most common due to various degradation. Noises in images are random variations in images due to lighting conditions, camera electronics, surface reflectance, lens, atmospheric conditions and motions (Either camera is moving or object is moving). Image Restoration is a process which restores a degraded image into its original image which has been degraded by some degradation model which degraded the image. Images are degraded due to various reasons. The first and foremost reason for image degradation is the fault in the imaging devices during the image acquisition process. The noise is generated in the imaging devices and is propagated to the image. The second source of degradation in image is the noise added during the image transmission. This type of image degradation is most common. The third source of image degradation is due to the motion blur and atmospheric turbulence. This paper analyzes various image noise models and restoration techniques. Particularly in analyses three kind of filters namely total variance filter, bilateral filter and wavelet image denoising. The image restoration is measured using the PSNR and SSI of original and degraded images