基于级数优化的小波去噪MAP图像复原方法

MAP Superresolution Restoration Algorithm based on Optimaized Order Basic Wavelet Denoising

介绍了MAP超分辨力复原方法的原理以及小波滤波去噪的原理和具体方法,由于小波变换具有多分辨率分析和在时频(空频)两域都具有表征信号局部特征的能力,基于小波阈值去噪的图像超分辨力复原方法对于低信噪比图像处理具有独特的优越性,证明了其应用于超分辨率复原算法的有效性,并提出了基于级数优化的小波去噪超分辨力复原算法。

MAP superresolution restoration algorithm and principle wavelet based on denoising are introduced. Because wavelet transform has characteristics of multireselution analysis and the capability of represent local signal feature in time -frenquecy （space -frenquecy） domain, the superreselution restoration algorithm based on wavelet threshold denosing has unique advantage for treating low SNR image. This article proved that it was effective for superresolution restoration and further propose a new superresolution algorithm based on optimal order wavelet denosing.