The invention discloses a low-illumination
image enhancement method based on multi-scale
frequency domain and position
perception. The method comprises the following steps: (1) preprocessing a low-illumination image, and converting the low-illumination image into an HVI
color space to decouple
chromaticity and brightness information; (2) respectively extracting characteristics of a chroma
branch and a brightness
branch by adopting a double-
branch backbone network; (3) inputting the extracted features into a multi-scale double-attention module to carry out multi-scale context aggregation and channel-space joint attention enhancement; (4) the features are sent to a complex value
frequency domain multilayer sensing module, the amplitude of the features is modulated in the
frequency domain to achieve global brightness modeling and
noise suppression, and meanwhile phase information is reserved to maintain structural details; (5) introducing explicit position coding between the
chromaticity branch and the brightness branch to guide feature interaction through a position awareness trans-attention module, and improving space consistency and color stability; and (6) fusing the double-branch enhanced features, converting the double-branch enhanced features back to the RGB space, and outputting a final enhanced image. According to the method, a multi-scale double-attention module is included, so that the multi-
scale structure representation capability is improved; the complex value frequency domain multilayer sensor module is used for realizing frequency domain
global modeling and effectively inhibiting high-
frequency noise artifacts under a low-light condition; a position sensing cross-attention module enhances the interspace adaptability of feature interaction between branches, thereby significantly improving the visual quality, structural fidelity and color stability of low-illumination
image enhancement, and reducing the problems of
noise amplification,
color shift and detail loss.