We propose an improvement of Sparse Sequence Matching Pursuit algorithm, namely Optimally Sequence Sparse Matching Pursuit (OpSSMP), through experiments in two perspectives that includes to reduce the number of measurement and to omit $K-sparse$ coefficient of signal. This is important to process various images which are different in number of sparse components so it plays an essential role when the algorithm maps to hardware. Although the running time of method is slower than SSMP, it remains comparable to state-of-the-art CoSaMP and SubSpace Pursuit algorithms.