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基于多路径交互的低光照图像增强。

Low-Light Image Enhancement Based on Multi-Path Interaction.

机构信息

School of Microelectronics, Tianjin University, Tianjin 300072, China.

School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China.

出版信息

Sensors (Basel). 2021 Jul 22;21(15):4986. doi: 10.3390/s21154986.

Abstract

Due to the non-uniform illumination conditions, images captured by sensors often suffer from uneven brightness, low contrast and noise. In order to improve the quality of the image, in this paper, a multi-path interaction network is proposed to enhance the R, G, B channels, and then the three channels are combined into the color image and further adjusted in detail. In the multi-path interaction network, the feature maps in several encoding-decoding subnetworks are used to exchange information across paths, while a high-resolution path is retained to enrich the feature representation. Meanwhile, in order to avoid the possible unnatural results caused by the separation of the R, G, B channels, the output of the multi-path interaction network is corrected in detail to obtain the final enhancement results. Experimental results show that the proposed method can effectively improve the visual quality of low-light images, and the performance is better than the state-of-the-art methods.

摘要

由于光照条件不均匀,传感器拍摄的图像往往存在亮度不均匀、对比度低和噪声等问题。为了提高图像质量,本文提出了一种多路径交互网络,分别对 R、G、B 三个通道进行增强,然后将三个通道合并为彩色图像,并进一步进行细节调整。在多路径交互网络中,使用几个编码-解码子网中的特征图在路径之间进行信息交换,同时保留一个高分辨率路径来丰富特征表示。同时,为了避免 R、G、B 三个通道分离可能导致的不自然结果,对多路径交互网络的输出进行了详细的修正,以获得最终的增强结果。实验结果表明,所提出的方法可以有效地提高低光照图像的视觉质量,性能优于现有方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a2f/8347206/431c10a079a4/sensors-21-04986-g001.jpg

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