Image denoising method based on adversarial generative network
An image and network technology, applied in the field of computer graphics and artificial intelligence, can solve the problems of image details, insufficient texture feature recovery, blind denoising of image noise, etc., to ensure the quality and reduce the effect of intervention
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[0026] The technical solutions in the implementation of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. It should be understood that the described examples are only some examples of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts belong to the protection scope of the present invention.
[0027] The invention provides an image denoising method based on an adversarial generation network through a conditional generation adversarial network. Image denoising is performed by building an adversarial generative network, the network structure is as follows figure 2 shown. Input the noise image and sample image into the adversarial network, and use the training idea of generative adversarial training to train the adversarial generation n...
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