Denoising millimeter wave image using contourlet and sparse coding shrinkage
Zhou Chang-xiong · Laser & Infrared · 2011
As for the problem of low resolution existing in millimeter wave(MMW)image,a new algorithm is proposed which combine the adaptive-self high-order statistical property of non-negative sparse coding(NNSC)algorithm and the contourlet′s composing orientation as well as the energy variation.The NNSC algorithm,developed in recent years,can efficiently simulate the information processing of human′s visual system.Using the feature basis vectors and the maximum likelihood estimation(MLE),the shrinkage denoising threshold can be determinate.Further,using this shrinkage technique in the contourlet′s transform field,the much unknown noise contained in millimeter wave image can be effectively reduced,and the quality of the restored MMW image can be improved.A clear natural image is used to prove the image restoration method based contourlet and NNSC shrinkage.The experimental results also testify the efficiency and usefulness of this image restoration method.This shows that our method can be used in restoring images with low resolution.