提出了一种基于分层树型结构正交匹配追踪算法的快速图像去噪方法。
A fast and efficient image denoising method is proposed based on Orthogonal matching pursuit which exploits the tree structure to reduce the complexity of the decomposition.
基于多种稀疏变换基和观测矩阵的组合，采用正交匹配追踪算法对图像进行重建。
Orthogonal Matching Pursuit (OMP) algorithm is used to reconstruct images based on the combinations of several common sparse transform bases and measurement matrices.
而子空间匹配追踪算法可以克服匹配追踪算法中的过匹配现象，加速了算法收敛速度，同时计算量比正交匹配追踪小得多。
SSMP can effectively overcome the over-matching phenomenon in the MP, improves the convergence rate, and has much less computation than the OMP.
在压缩感知框架下运用正则化正交匹配追踪(ROMP)算法进行图像重构时，迭代次数取值不合适会严重降低重构图像的质量。
The unsuitable iterative number of the Regularized Orthogonal Matching Pursuit (ROMP) algorithm in the framework of Compressive Sensing (CS) may reduce the quality of image reconstruction greatly.
在压缩感知框架下运用正则化正交匹配追踪(ROMP)算法进行图像重构时，迭代次数取值不合适会严重降低重构图像的质量。
The unsuitable iterative number of the Regularized Orthogonal Matching Pursuit (ROMP) algorithm in the framework of Compressive Sensing (CS) may reduce the quality of image reconstruction greatly.
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