摘要
提出一种基于多重稀疏表示的声纳图像超分辨率重建方法。该方法针对声纳图像的光滑、边缘和纹理3种结构形态,分别利用离散平稳小波变换、contourlet小波变换和Gabor小波变换建立过完备字典,并对多重稀疏表示的声纳图像进行超分辨率重建。实验结果表明,该方法得到的超分辨率图像能够有效保持原始高分辨率图像的几何特征和纹理特征,可以得到更高的峰值信噪比,并且对噪声具有鲁棒性。
A super-resolution reconstruction method for sonar image based on multi-layer sparse representation is proposed.As for the smooth,edge and texture of the sonar image,the discrete wavelet transform,the contourlet wavelet transform and the Gabor wavelet transform are used to establish the over-complete dictionary respectively.Then the multi-layer sparse represented sonar image is reconstructed in super-resolution.Experimental results show that the super-resolution images can maintain the geometric features and texture features of original high-resolution images effectively.Moreover,the proposed method is robust to noises and can achieve a higher peak signal to noise ratio compared with other methods.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2012年第1期204-207,共4页
Systems Engineering and Electronics
基金
国家自然科学基金(60904087)
黑龙江省博士后科技启动基金(LBH-Q09127)资助课题
关键词
超分辨率
稀疏表示
声纳图像
过完备字典
super-resolution
sparse representation
sonar image
over-complete dictionary
