Optimizing 4D Lookup Table for Low-light Video Enhancement via Wavelet Priori

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Hauptverfasser: He, Jinhong, Xue, Minglong, Wang, Wenhai, Zhou, Mingliang
Format: Preprint
Veröffentlicht: 2024
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author He, Jinhong
Xue, Minglong
Wang, Wenhai
Zhou, Mingliang
author_facet He, Jinhong
Xue, Minglong
Wang, Wenhai
Zhou, Mingliang
contents Low-light video enhancement is highly demanding in maintaining spatiotemporal color consistency. Therefore, improving the accuracy of color mapping and keeping the latency low is challenging. Based on this, we propose incorporating Wavelet-priori for 4D Lookup Table (WaveLUT), which effectively enhances the color coherence between video frames and the accuracy of color mapping while maintaining low latency. Specifically, we use the wavelet low-frequency domain to construct an optimized lookup prior and achieve an adaptive enhancement effect through a designed Wavelet-prior 4D lookup table. To effectively compensate the a priori loss in the low light region, we further explore a dynamic fusion strategy that adaptively determines the spatial weights based on the correlation between the wavelet lighting prior and the target intensity structure. In addition, during the training phase, we devise a text-driven appearance reconstruction method that dynamically balances brightness and content through multimodal semantics-driven Fourier spectra. Extensive experiments on a wide range of benchmark datasets show that this method effectively enhances the previous method's ability to perceive the color space and achieves metric-favorable and perceptually oriented real-time enhancement while maintaining high efficiency.
format Preprint
id arxiv_https___arxiv_org_abs_2409_08585
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Optimizing 4D Lookup Table for Low-light Video Enhancement via Wavelet Priori
He, Jinhong
Xue, Minglong
Wang, Wenhai
Zhou, Mingliang
Computer Vision and Pattern Recognition
Image and Video Processing
Low-light video enhancement is highly demanding in maintaining spatiotemporal color consistency. Therefore, improving the accuracy of color mapping and keeping the latency low is challenging. Based on this, we propose incorporating Wavelet-priori for 4D Lookup Table (WaveLUT), which effectively enhances the color coherence between video frames and the accuracy of color mapping while maintaining low latency. Specifically, we use the wavelet low-frequency domain to construct an optimized lookup prior and achieve an adaptive enhancement effect through a designed Wavelet-prior 4D lookup table. To effectively compensate the a priori loss in the low light region, we further explore a dynamic fusion strategy that adaptively determines the spatial weights based on the correlation between the wavelet lighting prior and the target intensity structure. In addition, during the training phase, we devise a text-driven appearance reconstruction method that dynamically balances brightness and content through multimodal semantics-driven Fourier spectra. Extensive experiments on a wide range of benchmark datasets show that this method effectively enhances the previous method's ability to perceive the color space and achieves metric-favorable and perceptually oriented real-time enhancement while maintaining high efficiency.
title Optimizing 4D Lookup Table for Low-light Video Enhancement via Wavelet Priori
topic Computer Vision and Pattern Recognition
Image and Video Processing
url https://arxiv.org/abs/2409.08585