Infrared-visible　image　fusion　plays　an　important　role　in　multi-source　data　fusion,　which　has　the　advantage　of　integrating　useful　information　from　multi-source　sensors.　However,　there　are　still　challenges　in　target　enhancement　and　visual　improvement.　To　deal　with　these　problems,　a　sub-regional　infrared-visible　image　fusion　method　(SRF)　is　proposed.　First,　morphology　and　threshold　segmentation　is　applied　to　extract　targets　interested　in　infrared　images.　Second,　the　infrared　back-ground　is　reconstructed　based　on　extracted　targets　and　the　visible　image.　Finally,　target　and　back-ground　regions　are　fused　using　a　multi-scale　transform.　Experimental　results　are　obtained　using　public　data　for　comparison　and　evaluation,　which　demonstrate　that　the　proposed　SRF　has　poten-tial　benefits　over　other　methods.