Enhancement of Low Light Level Images with coupled dictionary learning

• Published in: 2016 23rd International Conference on Pattern Recognition (ICPR) pp. 751 - 756
• Main Authors: Jie Yang, Xinwei Jiang, Chunhong Pan, Cheng-Lin Liu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2016
• Subjects: Brightness; Clustering algorithms; Dictionaries; Estimation; Histograms; Image reconstruction; Training
• DOI: 10.1109/ICPR.2016.7899725

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.