MMW Image Reconstruction Combined NNSC Shrinkage Technique and PDEs Algorithm

Abstract

For the problem that a millimeter wave (MMW) image contains noise and behaves low resolution, a novel MMW image reconstruction method, combined the non-negative sparse coding shrinkage (NNSCS) technique and the partial differential equations (PDEs) algorithm (denoted by NNSCS+ PDEs), is proposed in this paper. The method of PDEs is an efficient image reconstruction technique and is easy to implement. However, MMW image is highly contaminated by much unknown noise, and the reconstruction result is not satisfied only using PDEs to process images. While the NNSCS only relies on the high-order statistical property of an image and is a self-adaptive image denoising method. Thus, combined the advantage of NNSCS and PDEs, the MMW image can be well restored. In test, a natural image is used to testify the validity of the NNSC+PDEs method, and the signal noise ratio (SNR) is used as the measure criterion of restored images. Compared with NNSCS and PDEs respectively, simulation results show that our method is indeed efficient in the task of reconstructing WWM images.