TY - GEN
T1 - Reconstructing 3D Flame Temperature Fields via Light Field Compression, Denoising and Feature Extraction
AU - Wang, Qingran
AU - Gao, Pengfei
AU - Ren, Yatao
AU - Qi, Hong
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Accurate 3D temperature reconstruction is vital for combustion diagnostics under noisy conditions. This study develops a light field imaging framework incorporating a radiative transfer model and a Light Field Compression and Noise Reduction (LFCNR) method based on low-rank approximation and eigenvalue decomposition. The LFCNR algorithm separates signal and noise subspaces and applies Singular Value Decomposition (SVD) for structural compression, reducing computational complexity. Comparative results show that the customized 1D denoising with SVD truncation achieves superior accuracy (ARE = 2.8770%, NRMSE = 0.0408, SSIM = 0.9288), outperforming wavelet thresholding method (ARE = 2.9920%, NRMSE = 0.0429, SSIM = 0.9230). The framework ensures robust, high-resolution temperature reconstruction in complex combustion fields.
AB - Accurate 3D temperature reconstruction is vital for combustion diagnostics under noisy conditions. This study develops a light field imaging framework incorporating a radiative transfer model and a Light Field Compression and Noise Reduction (LFCNR) method based on low-rank approximation and eigenvalue decomposition. The LFCNR algorithm separates signal and noise subspaces and applies Singular Value Decomposition (SVD) for structural compression, reducing computational complexity. Comparative results show that the customized 1D denoising with SVD truncation achieves superior accuracy (ARE = 2.8770%, NRMSE = 0.0408, SSIM = 0.9288), outperforming wavelet thresholding method (ARE = 2.9920%, NRMSE = 0.0429, SSIM = 0.9230). The framework ensures robust, high-resolution temperature reconstruction in complex combustion fields.
KW - Combustion diagnostics
KW - Light field imaging
KW - Low-rank approximation
KW - Temperature tomography
UR - https://www.scopus.com/pages/publications/105034881345
U2 - 10.1109/CCPQT66408.2025.11383221
DO - 10.1109/CCPQT66408.2025.11383221
M3 - 会议稿件
AN - SCOPUS:105034881345
T3 - Proceeding of 2025 IEEE 4th International Conference on Computing, Communication, Perception and Quantum Technology, CCPQT 2025
BT - Proceeding of 2025 IEEE 4th International Conference on Computing, Communication, Perception and Quantum Technology, CCPQT 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE International Conference on Computing, Communication, Perception and Quantum Technology, CCPQT 2025
Y2 - 24 October 2025 through 26 October 2025
ER -