Enhancement of Low Light Level Images with coupled dictionary learning

Low Light Level Images (LLLIs) are captured with exceptionally low brightness and low contrast, and cannot be enhanced satisfactorily with ordinary methods. In this paper, we propose a LLLI enhancement method using coupled dictionary learning. During the training stage, a pair of dictionaries and a...

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Bibliographic Details
Published in2016 23rd International Conference on Pattern Recognition (ICPR) pp. 751 - 756
Main Authors Jie Yang, Xinwei Jiang, Chunhong Pan, Cheng-Lin Liu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2016
Subjects
Brightness
Clustering algorithms
Dictionaries
Estimation
Histograms
Image reconstruction
Training
Online AccessGet full text
DOI10.1109/ICPR.2016.7899725

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Summary:Low Light Level Images (LLLIs) are captured with exceptionally low brightness and low contrast, and cannot be enhanced satisfactorily with ordinary methods. In this paper, we propose a LLLI enhancement method using coupled dictionary learning. During the training stage, a pair of dictionaries and a linear mapping function are learned simultaneously. The dictionary pair aims to describe the raw LLLIs and their enhanced versions, and the linear mapping function models the correspondence between the representations of the dictionary pair. In the enhancement process, the resulting image is generated through dictionary mapping from patches of the input LLLI. We adopt a clustering strategy to improve the robustness of coupled dictionary learning, and propose an improved algorithm for fast implementation. Experimental results on real images demonstrate the effectiveness of our method.
DOI:10.1109/ICPR.2016.7899725