Abstract:

We present an image denoising method based on information geometry. Different than the traditional Euclidean space image denoising, the image denoising method based on information geometry makes use of manifold geodesic distance between two points to measure the similarities between two pixels in an image. The points on manifold are built by the Gaussian model of a region in an image and the geodesic distance between models represents the differences of average gray intensity and the detailed richness of the two image regions, in which way the similarities between pixels could be measured more accurately. Experiments show that the algorithm improves the denoising effect and maintains good image details.

Key words: information geometry;manifold;geodesic distance;Gaussian model;filtering