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Low-illuminance image enhancement method and system

An image enhancement and illumination technology, applied in the field of image processing, can solve the problems of weak generalization, color distortion, and weak detail processing ability, and achieve the effect of improving extraction ability, color distortion, and generalization.

Pending Publication Date: 2022-06-03
INST OF INTELLIGENT MFG GUANGDONG ACAD OF SCI
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  • Application Information

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Problems solved by technology

However, the existing enhancement methods often have problems such as color distortion, weak detail processing ability, and poor generalization.

Method used

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  • Low-illuminance image enhancement method and system

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Embodiment

[0050] figure 1 A schematic flowchart of a low-illumination image enhancement method in an embodiment of the present invention is shown, and the low-illumination image enhancement method includes:

[0051] S1: Input the low-light image into the convolutional neural network;

[0052]Input the low-light image into the convolutional neural network, and use some functions of the input layer, output layer, convolution layer, pooling layer and fully connected layer of the convolutional neural network to process the low-light image to enhance the image. According to the Retinex theory, the brightness of the object is decomposed into the reflection component of the object itself and the ambient light; since the color of the object perceived by vision only depends on the reflection ability of the object to the wavelength of light, and has nothing to do with the ambient light, therefore, it is estimated that when the image is collected, According to the light intensity component of the...

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Abstract

The invention discloses a low-illuminance image enhancement method and system, and the method comprises the steps: carrying out the multi-scale feature extraction of a low-illuminance image based on a plurality of convolution kernels, and carrying out the splicing of the multi-scale features, and obtaining a multi-size feature map; performing feature screening on the feature map by using a spatial attention mechanism to obtain a spatial attention feature map; mapping the spatial attention feature map based on three residual blocks connected in series to obtain high-dimensional features; performing weight processing on the high-dimensional features to obtain a channel attention feature map; carrying out channel reduction and logarithm operation on the channel attention features to obtain input image environment illumination component estimation; and processing the image according to the Retinex theory to obtain an enhanced image. According to the method, rich feature information of a low-illumination image is obtained through multi-scale convolution, the depth of the network is effectively deepened by using a residual block, image features are mapped to a high dimension, and the extraction capability of the network on significant information is improved by using space and channel attention in the network.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a low-illuminance image enhancement method and system. Background technique [0002] High-quality image acquisition is particularly important for computer vision tasks, such as target detection, image segmentation, text recognition, target tracking and other fields. Only by providing accurate image information can the successful completion of visual tasks be ensured. However, the change of shooting angle in an open environment, weak light in the morning and evening, and some special application scenarios will cause the camera's field of view to have problems such as low brightness, poor color saturation, and difficult to identify details. Improving low-light images through image enhancement has important implications for subsequent computer vision tasks. [0003] Low-light images widely exist in various computer vision tasks, and it is of great significance to enhance l...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06N3/04G06N3/08
CPCG06T5/00G06N3/08G06T2207/20081G06T2207/20084G06N3/048G06N3/045
Inventor 焦泽昱李辰潼黄天仑张勃兴马敬奇陈再励钟震宇
Owner INST OF INTELLIGENT MFG GUANGDONG ACAD OF SCI
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