2 February 2012 Image noise removal using image inpainting
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In this paper, new methods are addressed for impulse and speckle noise removal in images. The approach is based on the fusion of noise detection and image inpainting techniques. To avoid destroying the real structures of the image, the noise areas are first recognized to be repaired by an inpainting algorithm, subsequently. To distinguish the impulse noise areas in the image, a Neuro-Fuzzy model is employed and, to extract the speckled regions an algorithm is proposed based on Frost filtering and image resizing. The advantage of inpainting technique over the regular filtering methods is that it will be easier to generalize to all types of noise. Once we detect the damaged pixels in the image, the inpainting algorithm will be able to repair them. Various types of images under three levels of noise are tested using PSNR and SSIM measures. The experimental results demonstrate the great ability of the new approaches to suppress the noise properly, while preserving critical details of the image.
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Somayeh Bakhtiari, Elmira Mohyedinbonab, Sos Agaian, Mo Jamshidi, "Image noise removal using image inpainting", Proc. SPIE 8295, Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II, 82950N (2 February 2012); doi: 10.1117/12.906089; https://doi.org/10.1117/12.906089

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