【摘要】 针对基于压缩感知理论的红外图像重建问题,提出一种基于改进的分块压缩感知红外图像重建方法。该方法首先对原始红外图像进行分块,并对每个子块用相同的观测矩阵进行随机观测,获得少量的观测数据;然后利用谱图小波变换优异的稀疏特性,将其引入平滑投影Landweber算法进行迭代优化重建,同时采用混合中值滤波进行处理以增加图像的平滑度和减少块伪影,最后输出满足要求的高质量红外图像。实验结果表明,在相同采样率下,该方法对于不同类型红外图像的重建性能均优于目前广为采用的一些小波压缩感知方法,可获得更高质量的红外图像。更多还原

【Abstract】 Regarding to the reconstruction problem of an infrared image in compressed sensing,we proposed a modified block compressed sensing method.First,the original infrared image is divided into small blocks,each of which is sampled with a Gaussian random matrix to generate a small amount of measurement data.Second,Spectral Graph Wavelet transform with excellent sparse features is applied into reconstruction process of projected Landweber algorithm,and the hybrid median filter is used for enhancing image smoothness and reducing block artifacts.Finally,the high-quality infrared image satisfied termination conditions is obtained.Experimental results on various types of infrared images show that the proposed method attains much better performance in CS recovery than the conventional ones and can obtain higher quality infrared images.更多还原