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TSN-CA: A Two-Stage Network with Channel Attention for Low-Light Image Enhancement
In this paper, we propose a Two-Stage Network with Channel Attention (denoted as TSN-CA) to enhance the brightness of the low-light image and restore the enhanced images from various kinds of degradation.
DA-DRN: Degradation-Aware Deep Retinex Network for Low-Light Image Enhancement
We propose a Degradation-Aware Module (DA Module) which can guide the training process of the decomposer and enable the decomposer to be a restorer during the training phase without additional computational cost in the test phase.
BLNet: A Fast Deep Learning Framework for Low-Light Image Enhancement with Noise Removal and Color Restoration
We propose a Noise and Color Bias Control module (NCBC Module) that contains a convolutional neural network and two loss functions (noise loss and color loss).
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