线性非负约束的稀疏信号重建

Reconstructing Linear Nonnegative Constrained Sparse Signal

针对线性非负约束的稀疏信号重建问题,提出了基于线性规划的求解方法,充分考虑到信号的各种结构。通过图像仿真试验对比了该方法与传统方法,试验表明该方法性能更佳,可广泛应用于图像降噪、图像去模糊和医疗成像等。

Aimed at the problem of linear nonnegative constrained sparse signal reconstructing, a method based on linear programming is presented. The structures of signals are fully utilized in the method. Simulation experiments with images are developed to compare the method with the traditional method. Experimental results show the method has better performance and can be ap-plied in the field of image denoising, image deblurring, and medical imaging.