Randomized redundant DCT: efficient denoising by using random subsampling of DCT patches

Abstract

j In this paper, we propose an acceleration method for image denoising with a redundant discrete cosine transform (R-DCT). Image denoising is essential for image processing, and its efficiency is important for graphics applications. R-DCT with a hard-thresholding or shrinkage method can perform denoising while keeping detail textures. Moreover, the method is computationally efficient compared with state-of-the-art denoising methods, such as BM3D. The computational cost, however, is still insufficient for real-time processing; hence, we accelerate the method by using randomized subsampling of DCT patches. Experimental results show that our method can accelerate the processing while the degradation of denoising performance is a little.