A low-light image enhancement method and apparatus

An image enhancement and low-light technology, applied in the field of image processing, can solve problems such as noise amplification and achieve the effect of improving image quality

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An image enhancement and low-light technology, applied in the field of image processing, can solve problems such as noise amplification and achieve the effect of improving image quality

CN109087269AActive Publication Date: 2018-12-25XIAMEN MEITUZHIJIA TECH

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[0026] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments It is a part of the embodiments of this application, not all of them. The components of the embodiments of the application generally described and illustrated in the figures herein may be arranged and designed in a variety of different configurations.

[0027] Accordingly, the following detailed description of the embodiments of the application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of the application. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art w...

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Abstract

The embodiment of the present application provides a weak light image enhancement method and device. The method comprises respectively establishing a denoising network model, a color brightness conversion model and a detail enhancement network model, wherein the denoising network model, the color brightness conversion network model and the detail enhancement network model are all CNN models. The denoising network model, the color brightness transformation network model and the detail enhancement network model are trained respectively, and the denoising network model, the color brightness network model and the detail enhancement network model are trained jointly after the training is completed. After the joint training, the target low-light image data is processed by denoising network model, color-brightness transformation network model and detail enhancement network model, and the corresponding enhancement image is obtained. Thus, the image quality can be improved from denoising, colorbrightness transformation and detail enhancement.

Description

technical field [0001] The present application relates to the technical field of image processing, and in particular, to a low-light image enhancement method and device. Background technique [0002] In related technologies, low-light (low-illumination) image enhancement algorithms are roughly divided into three categories. One category is an enhancement algorithm based on histogram equalization, including DHE (Dynamic Histogram Equalization, DHE), Contrast Limited Adaptive Histogram Equalization (Contrast Limited Adaptive Histogram Equalization, CLAHE), Weighted Approximated Histogram Equalization (Weighted Approximated Histogram Equalization), Context and Variational Contast Enhancement (CVC), Layered Difference Representation (LDR), etc.; one class is based on retinal theory Enhancement algorithm, the other is the enhancement algorithm based on dehazing theory. In addition, there are some low-light image enhancement algorithms based on image fusion, but multiple low-ligh...

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Application Information

Patent Timeline

25 Dec 2018

Publication

CN109087269A

IPC: G06T5/00; G06N3/04

CPC: G06T2207/20084; G06T2207/10024; G06N3/045; G06T5/77; G06T5/70

Inventors: 周星光; 程安