Raw-to-Raw dark light image enhancement method

Abstract

The invention provides a Raw-to-Raw dark light image enhancement method, which comprises the following steps of: acquiring Raw data as a constructed training data set, and combining and expanding thetraining data set; building an image enhancement CNN network model according to the training data set, wherein the CNN network model comprises a multi-task training layer, an input layer, an encodingprocess, a decoding process, a jump connection layer and an output layer; performing iterative training on the CNN network model, updating each learnable parameter of the CNN network model to enable the learnable parameters to reach a certain convergence condition, and completing training; and performing model inference according to the trained CNN network model to finally obtain a dark light image enhancement network model, and performing image enhancement on the Raw data through the model. A dark light image enhancement model capable of intelligently processing a Raw format image is obtainedby constructing a data set and a model and training the data set and the model, so that the dark light image enhancement from Raw to Raw is realized.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a Raw-to-Raw low-light image enhancement method. Background technique [0002] Now, with the rapid development and wide application of multimedia technology and artificial intelligence, people use a lot of image information in their daily life. However, the current imaging technology is affected by low signal-to-noise ratio and low brightness under low-light conditions, and the image quality will be greatly affected. Image brightening, image repair and image enhancement are required to improve the visual effect of the image. Compared with the current image enhancement methods, there are problems such as underexposure, overexposure, blunt edge changes, discontinuity, serious noise, serious color deviation and other problems in the processing of dark light images. At the same time, the processing of Raw format images is also relatively inefficient. good questi...

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Problems solved by technology

[0004] In view of the deficiencies of the prior art above, the purpose of the present invention is to provide a Raw-to-Raw low-light image e

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