Hybrid reconstruction algorithm for computed tomography based on diagonal total variation

Inspired by total variation(TV), this paper represents a new iterative algorithm based on diagonal total variation(DTV) to address the computed tomography image reconstruction problem. To improve the quality of a reconstructed image, we used DTV to sparsely represent images when iterative convergence of the reconstructed algorithm with TV-constraint had no effect during the reconstruction process. To investigate our proposed algorithm, the numerical and experimental studies were performed, and rootmean-square error(RMSE) and structure similarity(SSIM)were used to evaluate the reconstructed image quality. The results demonstrated that the proposed method could effectively reduce noise, suppress artifacts, and reconstruct highquality image from incomplete projection data.

基于e^p的DTV图像去噪模型

针对纹理图像的去噪问题,通过分析全变分(TV)去噪模型与方向全变分(DTV)去噪模型,提出了一种具有鲁棒性的基于e^p的DTV去噪模型。为了刻画图像中的不同结构特征,该模型中DTV正则项的指数p由图像的结构来确定在(0,2)中自适应地选取。由于该模型是含有可分性算子的非光滑优化问题,可用交替方向乘子法(ADMM)求解,并能保证算法的收敛性。数值实验结果表明:与其他经典模型相比,提出的模型取得了更高的峰值信噪比和结构相似度,在去除噪声的同时能有效保持图像的细节信息。

基于分块对角矩阵的二维压缩感知数据采集和重构方法

针对遥感中线阵推扫数据采集模式和现有方法重构能力的不足,提出基于分块对角矩阵和TV(Total Variation)算法的二维压缩感知模型和方法。该方法能够使压缩感知的约束函数和目标函数同时包含完整的图像二维信息,是真正完全意义上的二维压缩感知。在不改变传统数据采集模式的基础上,通过分块对角矩阵的后处理,实现二维压缩感知。实验结果表明,该方法使图像的重构效果获得极大改善,SNR提高约8dB。但是该方法不适用于OMP(Orthogonal Matching Pursuit)和BP(Basis Pursuit)算法。该方法促进了定向遥感的发展,如与其他模型和方法结合,能进一步提高重构效果。