Image Restoration Model Using Total Variance, Bilateral and Wavelet Denoising Filter
Mohamed Abdul Kader Jailani N1, Thirunavukkarasu V2

1Mohamed Abdul Kader Jailani N, Faculty, Department of Computer science. CSA, REVA University, Bengaluru, India.
2Dr. V.Thirunavukkarasu, Faculty Department of computer science. CSA, REVA University, Bengaluru, India. 

Manuscript received on 01 August 2019. | Revised Manuscript received on 08 August 2019. | Manuscript published on 30 September 2019. | PP: 5888-5891 | Volume-8 Issue-3 September 2019 | Retrieval Number: C4731098319/19©BEIESP | DOI: 10.35940/ijrte.C4731.098319
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Abstract: 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.
Index Terms: Image Degradation, MSE and SSI, Total Variation Filter, Bilateral Filter, Wavelet denoising, PSF

Scope of the Article:
Image Security