Orthogonal Matching Pursuit (OMP) algorithm is used to reconstruct images based on the combinations of several common sparse transform bases and measurement matrices.
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。
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。
In the test stage, the sensing matrix is projected onto the test vector, and the minimum l0-norm solution is computed with Orthogonal Matching Pursuit (omp) algorithm.
利用正交匹配跟踪算法求最小零范数解，在变换域中用近邻法判断测试数据的类别。
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