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25 May 1989 Image Enhancement and Restoration Using Multiresolution Representations
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This paper uses multiresolution representations in two new techniques for image enhancement and restoration. The first method, based on image pyramids, is used for approximating the convolution of an image with a given mask. In this technique, a filter is designed using a least squares (ls) procedure based on filter functions synthesized from the basic pyramid equivalent filters. This approximates the mask frequency characteristic. Next, enhancement involves linearly combining scaled and filtered pyramid levels, using weights obtained from the is procedure. By this method, filtering and pyramid image coding can be combined, efficiently integrating enhancement into the reconstruction procedure for the coded image. The second method is an adaptive noise reduction algorithm. An optimally filtered image is synthesized from the multiresolution levels, which in this case, are maintained at the original sampling density. Individual pixels of the image representation are linearly combined under a minimum mean square error criterion. This uses a local signal to noise ratio estimate to provide the best compromise between noise removal and resolution loss.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Surendra Ranganath "Image Enhancement and Restoration Using Multiresolution Representations", Proc. SPIE 1092, Medical Imaging III: Image Processing, (25 May 1989);

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