Local adaptive transform based image de-noising with varying window size

Local adaptive image de-noising in transform domain is a powerfull tool for adapting to unknown smoothness of the images. In this work we propose to perform local adaptive denoising with adaptively varying local transform support size rather than using a transform with fixed size. We use a special rule antersection of Confidence Intervals - ICI) to select the optimum window sizes locally. The algorithm provides significant improvements in the de-noising performance.