Call For Paper Volume:4 Issue:10 Oct'2017 |

Image Denoising and Blind Deconvolution by Non-uniform Method

Publication Date : 30/04/2015



Author(s) :

B.Kalaiyarasi , S.Kalpana.


Volume/Issue :
Volume 2
,
Issue 4
(04 - 2015)



Abstract :

Image processing allows a much wider range of algorithms to be applied to the input data and can avoid problems such as the build-up of noise and signal distortion during processing of images. Iterative deblurring algorithm used in the existing technique mainly removes the blur caused during camera shake using the depth map but it does not focus on the noise present in the image. This paper presents a survey on different image filtering techniques. Image filtering is a crucial part of vision processing as it can remove noise from noisy images. There are many filtering techniques to filter an image. Here both linear and non-linear filters are employed for noise removal and sharpness enhancement. In this work four types of noise (Gaussian noise , Salt & Pepper noise, Speckle noise and Poisson noise) is used and image de-noising performed for different noise by Wiener filter, Median filter, Bilateral filter and Alpha trimmed mean filter. Decision based median filtering algorithm and alpha-trimmed mean filter algorithm gives promising results over salt and pepper noise. Further we have compared the different results on the basis of PSNR and MSE values of the restored image. Finally the conclusion is formulated. Thus we can reduce computational cost and prevent over-fitting.


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Image Denoising and Blind Deconvolution by Non-uniform Method

April 29, 2015