In　the　image　stitching　technology,　traditional　feature　extraction　algorithms　have　uneven　feature　points　distribution,　many　redundant　features,　time-consuming　feature　points　precision　matching　and　low　image　registration　accuracy.　In　view　of　these　problems,　this　paper　proposes　an　improved　image　registration　algorithm　based　on　BRISK　and　GMS.　In　this　method,　the　image　is　first　divided　into　meshes　and　BRISK　algorithm　is　used　for　extracting　image　features,　then　the　Brute　Force　matching　algorithm　is　used　for　rough　image　matching.　Finally,　the　mesh　motion　estimation　method　is　used　for　feature　quantity　statistics,　and　error　matching　is　removed　to　obtain　a　set　of　fine　matching　feature　points　for　image　registration.　This　paper　verified　the　robustness　of　the　improved　algorithm　by　comparing　it　with　other　methods　in　the　Mikolajczyk　data　set.　The　experimental　results　show　that　this　algorithm　achieves　higher　matching　accuracy　on　the　basis　of　maintaining　speed　compared　with　the　original　algorithm,　and　the　average　accuracy　is　improved　by　8.02%.　It　has　better　performance　than　the　traditional　algorithm,　which　can　be　used　for　occasions　with　higher　requirements　on　registration　accuracy　and　real-time　performance.　©　2019　IOP　Publishing　Ltd.　All　rights　reserved.