The　environment　of　flotation　site　is　harsh，and　the　lighting　conditions　are　complicated　and　variable.　For　the　flotation　images　collected　on-site　were　prone　to　underexposure，color　distortion，and　other　problems，a　low-illumination　image　color　depth　coding　and　decoding　correction　and　multiscale　enhancement　method　was　proposed.　First，the　low-illumination　image　was　converted　from　RGB　to　HSV　space，and　for　the　value（V）component，the　non-subsampled　shearlet　transform（NSST）was　used　to　perform　multi-scale　decomposition.　Second，a　color　depth　codec　correction　network　based　on　the　global　spatial　module　was　proposed，and　the　color　depth　coding　and　decoding　correction　network　model　was　constructed　through　squeeze　extraction，color　coding，color　decoding，and　color　correction.　Color　correction　was　performed　for　the　hue（H）and　saturation（S）components.　Then，the　low-frequency　subband　images　of　the　V　component　were　enhanced　by　adaptive　fuzzy　set，and　the　noise　components　of　each　high-frequency　sub⁃　band　image　of　the　V　component　were　effectively　filtered　out　using　the　scale　correlation　coefficient，while　the　high-frequency　edge　coefficients　were　significantly　enhanced　using　the　nonlinear　gain　function.　Finally，the　enhanced　images　of　the　various　subbands　of　the　V　component　were　reconstructed　by　the　inverse　trans⁃　form　of　the　NSST，and　the　reconstructed　V　component　was　fused　with　the　corrected　H　and　S　components　and　converted　back　to　RGB　space.　Experimental　results　demonstrate　that，compared　with　current　main⁃　stream　methods，the　proposed　method　achieves　an　average　reduction　of　14.　835　8　in　CIEDE，an　average　increase　of　8.　48　dB　in　PSNR，and　an　average　improvement　of　31.　32%　in　structural　similarity，with　the　continuous　edge　pixel　ratio　maintained　above　91%.　The　proposed　method　enhances　image　brightness，achieving　higher　contrast，clarity，and　information　entropy.　The　image　colors　are　closer　to　true　colors，preserving　more　texture　details，and　edges　are　enhanced　while　effectively　suppressing　noise.　©　2025　Chinese　Academy　of　Sciences.　All　rights　reserved.