Low-illumination color image enhancement method based on Retinex and convolutional neural network
A convolutional neural network and color image technology, applied in the field of low-light color image enhancement, can solve problems such as difficult to meet actual needs, distortion, noise color, etc.
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[0026] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, but the following embodiments do not limit the present invention in any way.
[0027] The invention proposes a low-light color image enhancement method based on Retinex and convolutional neural network. The design idea is to design three different convolutional neural networks, which are decomposition network, reflection map restoration network and illumination map adjustment network. The basic steps are: first input the low-light color image to the decomposition network designed by the present invention, and the decomposition network outputs a three-channel reflection map and a single-channel illumination map; then input the reflection map and illumination map to the reflection map restoration network , perform denoising and color restoration processing, and obtain the restored reflection map; then input the light map and light adjustment paramet...
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