Orthogonal Matching Pursuit (OMP) is a greedy algorithm used for sparse approximation of signals, particularly within the framework of compressed sensing. It iteratively selects the most correlated dictionary elements with the target signal, updating the approximation and refining the residual error at each step. OMP is significant in efficiently recovering high-dimensional signals from limited measurements, making it a powerful tool in various applications like image reconstruction and signal processing.
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