HDR+ PyTorch

This is a simplified PyTorch implementation of HDR+, the backbone of computational photography in Google Pixel phones, described in Burst photography for high dynamic range and low-light imaging on mobile cameras. Using a free Colab GPU, aligning 20MP RAW images takes ~200 ms/frame.

If you would like to use HDR+ in practice (rather than research), please check out my open-source Mac app Burst Photo. It has a GUI, supports robust merge, and uses Adobe DNG SDK (instead of LibRaw), significantly improving image quality.

Example

I took a burst of 35 images at ISO 12,800 on Sony RX100-V and boosted it by +2EV. Here's a comparison of a single image from the burst vs. a merge of all the images.

Usage

Here's a minimal example to align and merge a burst of raw images. For more, see the Colab Notebook.

import torch, align
images = torch.zeros([5, 1, 1000, 1000])
merged_image = align.align_and_merge(images)

Implementation details

The implementation heavily relies on first class dimensions, which allows for vectorized code that resembles the use of explicit loops. Previous versions of this repo used standard NumPy-style broadcasting but that was slower, harder to read, and required more loc.

Features

• jpeg support
• RAW support
• simple merge
• robust merge
• tile comparison in pixel space
• tile comparison in Fourier space
• CUDA support
• CPU support (very slow)
• color post-processing
• automatic selection of the reference image

Citation

@article{hasinoff2016burst,
  title={Burst photography for high dynamic range and low-light imaging on mobile cameras},
  author={Hasinoff, Samuel W and Sharlet, Dillon and Geiss, Ryan and Adams, Andrew and Barron, Jonathan T and Kainz, Florian and Chen, Jiawen and Levoy, Marc},
  journal={ACM Transactions on Graphics (ToG)},
  volume={35},
  number={6},
  pages={1--12},
  year={2016},
  publisher={ACM New York, NY, USA}
}