Aerial　imaging　aims　to　produce　well-exposed　images　with　rich　details.　However,　aerial　photography　may　encounter　low-light　conditions　during　dusk　or　dawn,　as　well　as　on　cloudy　or　foggy　days.　In　such　low-light　scenarios,　aerial　images　often　suffer　from　issues　such　as　underexposure,　noise,　and　color　distortion.　Most　existing　low-light　imaging　methods　struggle　with　achieving　realistic　exposure　and　retaining　rich　details.　To　address　these　issues,　we　propose　an　Aerial　Low-light　Imaging　with　Color-monochrome　Engagement　(ALICE),　which　employs　a　coarse-to-fine　strategy　to　correct　low-light　aerial　degradation.　First,　we　introduce　wavelet　transform　to　design　a　perturbation　corrector　for　coarse　exposure　recovery　while　preserving　details.　Second,　inspired　by　the　binocular　low-light　imaging　mechanism　of　the　Human　Visual　System　(HVS),　we　introduce　uniformly　well-exposed　monochrome　images　to　guide　a　refinement　restorer,　processing　luminance　and　chrominance　branches　separately　for　further　improved　reconstruction.　Within　this　framework,　we　design　a　Reference-based　Illumination　Fusion　Module　(RIFM)　and　an　Illumination　Detail　Transformation　Module　(IDTM)　for　targeted　exposure　and　detail　restoration.　Third,　we　develop　a　Dual-camera　Low-light　Aerial　Imaging　(DuLAI)　dataset　to　evaluate　our　proposed　ALICE.　Extensive　qualitative　and　quantitative　experiments　demonstrate　the　effectiveness　of　our　ALICE,　achieving　a　PSNR　improvement　of　at　least　19.52%　over　12　state-of-the-art　methods　on　the　DuLAI　Syn-R1440　dataset,　while　providing　more　balanced　exposure　and　richer　details.　Our　codes　and　datasets　are　available　at　https://github.com/yuanpengwu1/ALICE.