Binocular　camera　calibration　is　the　foundation　of　stereo　vision　research,　and　its　accuracy　is　the　key　to　achieve　precision　in　vision　measurement.　The　basis　of　camera　calibration　is　image　corner　extraction,　but　in　real　applications,　the　accuracy　of　detected　corner　points　is　often　low　due　to　unclear　acquisition　of　images　due　to　external　influences,　which　affects　calibration　accuracy.　To　solve　the　problem　of　low-quality　corner　detection　in　terms　of　the　feature　level,　an　end-to-end　algorithm　based　on　super-resolution　subpixel　corner　detection　is　proposed.　First,　the　fuzzy　kernel　of　a　low-resolution　image　is　estimated　using　the　blind　hyperspectral　part,　and　its　features　are　fused　to　reconstruct　its　high-resolution　version.　Subsequently,　the　subpixel　position　of　the　corner　points　is　obtained.　Finally,　a　binocular　camera　is　calibrated　with　high　accuracy　and　tested　via　ranging　experiments.　Experimental　results　show　that　the　proposed　subpixel　corner　detection　method　based　on　super-resolution　has　advantages　in　real　scenarios.　©　2023　Universitat　zu　Koln.　All　rights　reserved.