A Restoration Method of Infrared Image Based on Compressive Sampling

The deluge of big data is changing the operational environments of many sampling system. Modern technology is in the dangerous of submersion by big data. The paper investigated the present situation of infrared image processing techniques. An applied of compressive sampling to restoration of infrared image is given for denoising and deblurring tasks. In convex optimization stage, the fixed point continuation (FPC) is employed. Finally, the subjective and objective index is applied in the evaluation of proposed method. The PSNR (Peak Signal to Noise Ratio) and MSSIM (Mean Structural Similarity) are used to evaluate the performance of those methods. Experimental tests are executed by using infrared image of person in sand dune. Comparing with other existing methods, the proposed give the satisfying performance. It can provide a reference to practical engineering.