The invention discloses an image
rain removal method based on phase
perception and dynamic optimization, and the method comprises the steps: constructing a phase
perception dynamic
rain removal network, converting a rain-containing image into a rain-containing image of a large-resolution flow, a medium-resolution flow and a small-resolution flow, and carrying out the
parallel processing of the rain-containing image; channel attention operation is carried out on space, frequency and biological visual features to generate multi-
modal fusion features, the multi-
modal fusion features are combined with rain-containing image input features of various resolutions to generate decoding features, details are reconstructed through INR after fusion, preliminary
rain removal features are output, and raindrop complexity is evaluated to dynamically optimize and output rain removal images; when the phase
perception dynamic rain removal network is trained, network parameters are optimized through a composite
loss function; and inputting a to-be-processed rain-containing image into the trained phase perception dynamic rain removal network for multi-scale feature
processing and dynamic optimization refinement, and outputting a clear image after rain removal. According to the invention, multi-
modal feature fusion, dynamic rain condition
adaptation and high-precision detail
recovery are realized.