A　semiglobal　stereo　matching　algorithm　based　on　fusion　cost　and　adaptive　penalty　coefficient　is　proposed　to　address　the　low-accuracy　problem　of　semi-global　stereo　matching　algorithms　in　discontinuous　disparity　regions.　In　the　cost　calculation　part,　a　fusion　cost　calculation　method　is　proposed　introducing　the　gradient　in　the　y　direction　of　the　input　image　and　combining　the　fusion　formula　with　the　gradient　in　the　x　direction　of　the　input　image,　absolute　difference,　and　Census　transform　to　form　the　cost　calculation　data　item;　in　the　cost　aggregation　part,　a　pixel　classification　mechanism　is　proposed　that　classifies　each　pixel　by　color　and　gradient　dual　thresholds　and　adaptively　adjusts　the　size　of　its　penalty　coefficients;　finally,　the　initial　parallax　map　is　processed　using　a　multistep　parallax　optimization　method.　Results　show　that　the　average　error　of　the　proposed　algorithm　in　the　discontinuous　parallax　regions　decreases　by　1.　1　percentage　points　to　12.　8　percentage　points,　and　it　also　decreases　in　non-occlusion　and　all　regions.　The　proposed　algorithm　exhibits　high　matching　accuracy　and　robustness.　©　2022　Universitat　zu　Koln.　All　rights　reserved.