Paper
2 May 2024 Proposal of an improved loss function considering image-edge structure for DNN-based video prediction
Author Affiliations +
Proceedings Volume 13164, International Workshop on Advanced Imaging Technology (IWAIT) 2024; 131640D (2024) https://doi.org/10.1117/12.3018046
Event: International Workshop on Advanced Imaging Technology (IWAIT) 2024, 2024, Langkawi, Malaysia
Abstract
Introduction of loss function that considers image structure to DNN-based video prediction has been proven to reduce blurriness of generated prediction frames. In this paper, we propose an improved loss function based on image gradient difference (GDL) which captures edge structure of image, and evaluate its performance over PredNet that is a well-known DNN-based video prediction scheme. Our experimental results show that the proposed loss function can improve prediction performance in terms of color representation and generating sharper prediction frames.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Hiroki Nishimura, Shunichi Sekiguchi, and Wataru Kameyama "Proposal of an improved loss function considering image-edge structure for DNN-based video prediction", Proc. SPIE 13164, International Workshop on Advanced Imaging Technology (IWAIT) 2024, 131640D (2 May 2024); https://doi.org/10.1117/12.3018046
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KEYWORDS
Video

Gas lasers

Visualization

Education and training

Signal attenuation

Image quality

Image enhancement

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