Underwater image enhancement method based on conditional generative adversarial network
An underwater image, conditional generation technology, applied in image enhancement, biological neural network model, image analysis, etc., can solve the problems of lack of details in synthetic images, poor practical generalization ability, color distortion, etc.
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[0045] The embodiment of the present invention will be explained in detail below in conjunction with the accompanying drawings. The examples given are only for the purpose of illustration, and cannot be interpreted as limiting the present invention. The accompanying drawings are only for reference and description, and do not constitute the scope of patent protection of the present invention. limitations, since many changes may be made in the invention without departing from the spirit and scope of the invention.
[0046] (1) Method description
[0047] The purpose of the underwater image enhancement task is to process a low-quality underwater image (denoted as X) through a series of processes to obtain a high-quality and clear image (denoted as Y), which can be classified as from an image (turbid water quality) to Image translation issue for another image (clear water quality). The underwater image enhancement task can be seen as finding a way to learn a mapping relationship ...
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