Hyperspectral image deep noise reduction method and system based on two-stage learning framework

The invention discloses a hyperspectral image depth noise reduction method and system based on a two-stage learning framework, and belongs to the technical field of hyperspectral image noise reduction, and a three-dimensional depth universal model 3D-DUSSD for hyperspectral image noise reduction comprises the following steps: constructing a target function based on noise estimation and image noise reduction; constructing a conditional estimation sub-network (CENet) and a multi-scale cross fusion noise reduction sub-network based on a target function; training a conditional estimation sub-network (CENet) and a multi-scale cross fusion noise reduction sub-network by using an objective function; the trained conditional estimation sub-network (CENet) is utilized to deduce the noise level of the hyperspectral image, and then information is transmitted into the multi-scale cross fusion noise reduction sub-network to carry out the denoising of the hyperspectral image. By means of the method, non-i. I. D. Noise distr