Aiming　at　the　problem　of　slow　algorithmic　stitching　and　low　accuracy　due　to　the　existence　of　a　large　number　of　similar　and　neatly　arranged　LEDs　in　the　existing　microscopic　images　of　Micro-LED　chips，this　paper　proposed　a　clustering-based　Micro-LED　chip　micro-image　stitching　method.　Firstly，the　OTSU　method　was　used　to　preprocess　the　images，and　then　the　adaptive　area　expansion　phase　correlation　method　was　used　to　peak　the　overlapping　regions　of　two　adjacent　images　to　obtain　the　offset　of　the　preliminary　alignment.　Subsequently，the　optimized　alignment　strategy　using　image　chunking　and　the　DHash　algorithm　was　employed　to　obtain　the　optimized　offset.　Finally，density-based　spatial　clustering　of　applications　with　noise　was　introduced　to　automatically　screen　out　and　deal　with　the　possible　erroneous　offsets.　The　experimental　results　show　that　the　average　time　consumption　of　this　paper＇s　algorithm　is　64　ms，which　meets　the　demand　of　real-time　stitching，the　stitching　correct　rate　reaches　99.　4%，the　alignment　accuracy　is　controlled　within　1　pixel，and　the　fusion　processing　can　achieve　a　perfect　stitching　effect　subjectively，which　also　provides　a　new　solution　to　the　overall　misalignment　problem　caused　by　the　wrong　offsets.　The　algorithm　in　this　paper　effectively　solves　the　key　link　of　microscopic　image　stitching　in　wafer-level　Micro-LED　chip　inspection　and　can　be　promoted　and　applied　to　other　machine　vision　automation　fields　with　repetitive　features　and　high　precision　requirements，with　high　practical　engineering　application　value.　©　2025　Chinese　Academy　of　Sciences.　All　rights　reserved.