A Coding Scheme for Noisy Image Based on Layer Segmentation

Abstract

Heavy noises distribute in the images when imaging in a poor environment. The randomness of noises makes pixels distributing singularly, which weakens the 1-D piecewise smooth property of original scenes. Thus, wavelets-based compression method no longer works well. In this paper, a layer segmentation based compression scheme is proposed for gray images. Image textures and some high frequency noises are described in a high frequency layer while the coarse part of the image is described in the low frequency layer. The high frequency layer is represented by a joint dictionary, and the low frequency layer is coded with the traditional wavelets. The proposed scheme is tested on nature images and synthetic images. The results show that the proposed scheme achieves better rate-distortion performance compared with several competing compression systems. Besides, further degradation of edges is avoided by the proposed compression scheme.