Alpha-rooting color image enhancement for neural light field rendering

Emmanuel Oluga; Ben Young; R. Lyle Hood; Artyom M. Grigoryan

doi:10.1117/12.2663273

15 June 2023 Alpha-rooting color image enhancement for neural light field rendering

Emmanuel Oluga, Ben Young, R. Lyle Hood, Artyom M. Grigoryan

Proceedings Volume 12526, Multimodal Image Exploitation and Learning 2023 ; 125260G (2023) https://doi.org/10.1117/12.2663273
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Conference Poster

Abstract

In this paper, we explore the use of low-light image enhancement as a preprocessing step to improve the quality of novel view synthesis by Neural Light Fields (NeLF). NeLF is a 3D scene representation method that employs a light field representation, differing from prior methods based on volumetric rendering schemes. One of the main advantages of NeLF is its faster rendering speed, as it requires only one network forward pass without Ray marching. However, NeLF struggles to model low-illumination scenes due to its viewer-centered framework, which does not consider the interaction between illumination and scenes. To address this issue, we propose the use of 2D low-light image enhancement as a preprocessing solution. Our approach utilizes the Alpha-rooting by 2-D DFT as a preprocessing step to enhance low-light images prior to their use by the NeLF model. We demonstrate that this approach leads to significant improvements in the quality of novel view synthesis by NeLF on low-light images. We also consider how this can have practical applications in various domains such as applied human biomechanics.

Citation Download Citation

Emmanuel Oluga, Ben Young, R. Lyle Hood, and Artyom M. Grigoryan "Alpha-rooting color image enhancement for neural light field rendering", Proc. SPIE 12526, Multimodal Image Exploitation and Learning 2023 , 125260G (15 June 2023); https://doi.org/10.1117/12.2663273

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