In　order　to　improve　the　success　rate　and　reconstruction　accuracy　of　the　compressed　sensing　reconstruction　algorithm,　the　Look　Ahead　and　Regular　Backtracking　Orthogonal　Matching　Pursuit　based　on　Dice　coefficient　(DLARBOMP)　is　proposed.　In　this　algorithm,　from　the　perspective　of　matching　criteria　and　atom　selection　in　the　pre-selection　stage,　the　Dice　coefficient　is　used　to　replace　the　atomic　inner　product　to　calculate　the　correlation　value　and　preserve　the　characteristics　of　the　original　signal,　to　select　the　atom　that　best　matches　the　residual　and　improve　the　reconstruction　accuracy.　At　the　same　time,　to　reduce　backtracking　time　in　the　reconstruction　process,　regularization　is　used　to　select　multiple　atoms　instead　of　a　single　atom　in　each　iteration,　achieving　a　balance　between　reconstruction　accuracy　and　time.　Finally,　the　experimental　results　of　sparse　one-dimensional　signal　and　two-dimensional　image　signal　reconstruction　show　that　the　proposed　DLARBOMP　algorithm　considers　both　performance　and　efficiency　when　reconstructing　one-dimensional　signal,　and　enhances　the　Peak　Signal-to-Noise　Ratio　(PSNR)　when　reconstructing　two-dimensional　compressed　image　signal,　as　compared　to　Orthogonal　Matching　Pursuit　(OMP)　and　the　state-of-the-art　greedy　algorithms.　©　2024　Science　Press.　All　rights　reserved.