2014/11/20 by Victor May, Yosi Keller, May, Victor +5
Computer Science · Engineering · Mathematics · #Advanced Image Fusion Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Mathematics #General Mathematics (math.GM) #Image and Signal Denoising Methods #Medical Image Segmentation Techniques #Sparse and Compressive Sensing Techniques #Statistical and numerical algorithms #cs.CV #math.GM
paper · pdf · doi:10.48550/arxiv.1412.2067
arxiv created 2014/11/20 · openalex publication_date 2014/11/20 · arxiv updated 2014/12/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We present a method for improving a Non Local Means operator by computing its low-rank approximation. The low-rank operator is constructed by applying a filter to the spectrum of the original Non Local Means operator. This results in an operator which is less sensitive to noise while preserving important properties of the original operator. The method is efficiently implemented based on Chebyshev polynomials and is demonstrated on the application of natural images denoising. For this application, we provide a comprehensive comparison of our method with leading denoising methods.