Optical aberrations Correction in Postprocessing using Imaging Simulation (TOG 2021, PostRec. SIGGRAPH 2022)
by Shiqi Chen, Huajun Feng, Dexin Pan, Zhihai Xu, Qi Li, and Yueting Chen
This is the official Pytorch implementation of "Optical aberrations Correction in Postprocessing using Imaging Simulation" [Paper]
🚩 Updating（New Features/Updates）
- ✅ Oct. 19, 2023. Add the illustration of psf calculation and the script of analysis module in ray tracing.
import torch
import difftrace as dg
# load the lens
device = torch.device('cpu')
dtype = torch.float64
lens = dg.System('lens_file/doubleGauss.json', torch.float64, torch.device('cpu'))
# define analysis
views = torch.tensor([0., 10., 14.], dtype=dtype, device=device)
wavelengths = torch.tensor([dg.lambda_F, dg.lambda_d, dg.lambda_C], dtype=dtype, device=device)
ana = dg.Analysis(lens, views, wavelengths, dtype=dtype, device=device)import matplotlib.pyplot as plt
pupil_sampling = 201
image_sampling = 101
image_delta = 0.0005
sample_distribution = 'hexapolar'
psf_kirchoff = ana.psf_kirchoff(pupil_sampling=pupil_sampling,
image_sampling=image_sampling,
image_delta=image_delta)
plt.imshow(psf_kirchoff, cmap='jet')here we optimize the precalculation of the entrace pupil and the rays sampling, so be free to directly use this method
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent