The present application relates to the technical field of
image processing, and discloses a physical guiding low-light
image enhancement method based on joint modeling of illumination and
exposure, wherein a low-light image to be processed is input into an illumination and
exposure prediction module to perform
feature extraction and generate a
local illumination map, and a global
exposure factor is derived based on the
local illumination map; the low-light image to be processed, the
local illumination map and the global exposure factor are input into a double condition adaptive enhancement module,
intensity modulation is performed in combination with the global exposure factor, spatially guided interactive operation is performed in combination with the local illumination map, and an enhanced image is output after feature reconstruction; in the model training stage, a normal light
reference image is acquired, reconstruction loss and
structural consistency loss are calculated, exposure consistency loss is calculated for the global exposure factor, and an overall
loss function is constructed to drive an optimizer to jointly optimize network parameters. The present application realizes adaptive calibration of
local space and global brightness, effectively suppresses
image noise while recovering dark details.