LightenNet: a Convolutional Neural Network for weakly illuminated image enhancement
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Li, Chongyi; Guo, Jichang; Porikli, Fatih; Pang, Yanwei
Description
Weak illumination or low light image enhancement as pre-processing is needed in many computer vision tasks. Existing methods show limitations when they are used to enhance weakly illuminated images, especially for the images captured under diverse illumination circumstances. In this letter, we propose a trainable Convolutional Neural Network (CNN) for weakly illuminated image enhancement, namely LightenNet, which takes a weakly illuminated image as input and outputs its illumination map that is...[Show more]
Collections | ANU Research Publications |
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Date published: | 2017 |
Type: | Journal article |
URI: | http://hdl.handle.net/1885/139409 |
Source: | Pattern Recognition Letters |
DOI: | 10.1016/j.patrec.2018.01.010 |
Access Rights: | Open Access |
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