Comparison and Study of Different Image Denoising Techniques
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 10
Abstract
Image denoising is a technique which removes out noise which is added in the original image. Noise reduction is an important part of image processing systems. An image is always affected by noise. Image quality may get disturbed while capturing, processing and storing the image. Noise is nothing but the real world signals and which are not part of the original signal. Removal of noise is an important step in the image restoration process, and remains a challenging problem in spite of the sophistication of recent research. Image denoising involves the manipulation of the image data to produce a visually high quality image. This report presents a comparison of three image denoising methods, all minimizing the variation of an image – Dualtree complex DWT,Surelet denoising method and Bayes estimate denoise method. These algorithms are compared based on their assumptions and shortcomings using a methodology that examines the Peak signal-to-noise ratio (PSNR), Mean Square Error (MSE) ,Structural Similarity Index (SSIM) and overall quality of the denoised image.
Authors and Affiliations
Nijisha P
Keywords
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