The invention discloses a twin network image denoising method and system based on Transform, a medium and equipment, and designs two twin networks to extract complementary features, so that the robustness of an obtained denoising device is stronger. Transform is applied to a twin network, saliency features are extracted, a foreground and a background are separated, noise is removed, and a clean image is predicted; a cross interaction mechanism is designed to improve the memory ability of the deep network, and the denoising performance is improved; according to the method, batch normalization, layer normalization, instance normalization, a Swsh function and a linear rectification function activation function component are used in the twin network, so that the learning ability of the denoising network is improved, diversified features can be extracted, the denoising effect is enhanced, and the denoising efficiency is improved. In addition, denoising is carried out only through a 12-layer network, the calculation cost of the network is greatly reduced, and the requirements of mobile equipment are met very well. And saliency features can be adaptively extracted according to different scenes, and the method has a blind denoising function and a relatively high practical application value.