LiU HDRv Repository - Resources
Computer Graphics and Image Processing
Visual Computing Laboratory

Gallery & Resources

Here you can find a large number of HDRv examples and different resources to download.
The resources that we are making available include:

- HDRv sequences and frames
- HDR-video light probe sequences that can be used for image based lighting
- Static high resolution HDR panoramas with background images from the capture environment
- Software and code (WebGL HDR viewer)

All data, code and other information in the HDRv repository may be used freely under the terms of the creative commons license CC BY-SA 4.0.

HDRv sequences

Below, we display a number of example sequences captured using our HDRv imaging systems. The sequences are captured in different environments.

Each full resolution frame from our HDRv sequences is around 45 MB in size. The sequences have therefore been downsampled to 720p, i.e. 1280x720 pixels. All frames are stored in the OpenEXR file format.

HDR-video sequence: Astronauts

Tone mapped preview (best viewed in fullscreen)

View a single frame in our online HDR image viewer:
[High resolution] (6.1 MB), [Low resolution] (1.5 MB)
(Requires a WebGL enabled web browser.)

Sequence information:
This HDR-video sequence captured in the Visual Computing Lab, Norrköping Visualization Centre -C in Sweden using a Nikon f/1.4D 50mm Nikkor lens. The sequence was captured using the methods and algorithms described in:

J. Kronander, S. Gustavson, G. Bonnet, J. Unger: Unified HDR Reconstruction from RAW CFA Data, In proceedings of the International Conference on Computational Photography (ICCP), 2013, Harvard University, Cambridge, USA, April, 2013.

J. Kronander, S. Gustavson, G. Bonnet, A. Ynnerman, J. Unger: A Unified Framework for Multi-Sensor HDR Video Reconstruction, Accepted for publication in Signal Processing: Image Communications, 2013

The images are not calibrated to represent absolute scene luminance measurements.

Download HDR-sequence as OpenEXR frames (720p): Astronauts.zip (749 MB)
If you wish to use this video sequence in your research, we kindly ask you cite the papers mentioned above.

HDR-video sequence: Campus Norrköping Window

Tone mapped preview (best viewed in fullscreen)

Sequence information:
This HDR-video sequence was captured at Campus Norrköping at Linköping University in Sweden. The sequence was radiometrically calibrated using a Photo Research PR-650 photospectrometer. The sequence was captured using the methods and algorithms described in:

J. Kronander, S. Gustavson, G. Bonnet, J. Unger: Unified HDR Reconstruction from RAW CFA Data, In proceedings of the International Conference on Computational Photography (ICCP), 2013, Harvard University, Cambridge, USA, April, 2013.

J. Kronander, S. Gustavson, G. Bonnet, A. Ynnerman, J. Unger: A Unified Framework for Multi-Sensor HDR Video Reconstruction, Accepted for publication in Signal Processing: Image Communications, 2013

and originally used in the project:

Gabriel Eilertsen, Robert Wanat, Rafal Mantiuk, Jonas Unger: Evaluation of tone mapping operators for HDR-video, In Computer Grahpics Forum Special Issue Proceedings of Pacific Graphics, Singapore, 7-9 October, 2013.

Download HDR-sequence as OpenEXR frames (720p): window.zip (692 MB)
If you wish to use this video sequence in your research, we kindly ask you cite the papers mentioned above.

HDR-video sequence: Students

Tone mapped preview (best viewed in fullscreen)

Sequence information:
This HDR-video sequence was captured at Campus Norrköping at Linköping University in Sweden. The sequence was radiometrically calibrated using a Photo Research PR-650 photospectrometer. The sequence was captured using the methods and algorithms described in:

J. Kronander, S. Gustavson, G. Bonnet, J. Unger: Unified HDR Reconstruction from RAW CFA Data, In proceedings of the International Conference on Computational Photography (ICCP), 2013, Harvard University, Cambridge, USA, April, 2013.

J. Kronander, S. Gustavson, G. Bonnet, A. Ynnerman, J. Unger: A Unified Framework for Multi-Sensor HDR Video Reconstruction, Accepted for publication in Signal Processing: Image Communications, 2013

and originally used in the project:

Gabriel Eilertsen, Robert Wanat, Rafal Mantiuk, Jonas Unger: Evaluation of tone mapping operators for HDR-video, In Computer Grahpics Forum Special Issue Proceedings of Pacific Graphics, Singapore, 7-9 October, 2013.

Download HDR-sequence as OpenEXR frames (720p): students.zip (740 MB)
If you wish to use this video sequence in your research, we kindly ask you cite the papers mentioned above.

HDR-video sequence: Campus Norrköping Hallway

Tone mapped preview (best viewed in fullscreen)

Sequence information:
This HDR-video sequence was captured at Campus Norrköping at Linköping University in Sweden. The sequence was radiometrically calibrated using a Photo Research PR-650 photospectrometer. The sequence was captured using the methods and algorithms described in:

J. Kronander, S. Gustavson, G. Bonnet, J. Unger: Unified HDR Reconstruction from RAW CFA Data, In proceedings of the International Conference on Computational Photography (ICCP), 2013, Harvard University, Cambridge, USA, April, 2013.

J. Kronander, S. Gustavson, G. Bonnet, A. Ynnerman, J. Unger: A Unified Framework for Multi-Sensor HDR Video Reconstruction, Accepted for publication in Signal Processing: Image Communications, 2013

and originally used in the project:

Gabriel Eilertsen, Robert Wanat, Rafal Mantiuk, Jonas Unger: Evaluation of tone mapping operators for HDR-video, In Computer Grahpics Forum Special Issue Proceedings of Pacific Graphics, Singapore, 7-9 October, 2013.

Download HDR-sequence as OpenEXR frames (720p): hallway.zip (914 MB)
If you wish to use this video sequence in your research, we kindly ask you cite the papers mentioned above.

HDR-video sequence: Campus Norrköping Hallway 2

Tone mapped preview (best viewed in fullscreen)

Sequence information:
This HDR-video sequence was captured at Campus Norrköping at Linköping University in Sweden. The sequence was radiometrically calibrated using a Photo Research PR-650 photospectrometer. The sequence was captured using the methods and algorithms described in:

J. Kronander, S. Gustavson, G. Bonnet, J. Unger: Unified HDR Reconstruction from RAW CFA Data, In proceedings of the International Conference on Computational Photography (ICCP), 2013, Harvard University, Cambridge, USA, April, 2013.

J. Kronander, S. Gustavson, G. Bonnet, A. Ynnerman, J. Unger: A Unified Framework for Multi-Sensor HDR Video Reconstruction, Accepted for publication in Signal Processing: Image Communications, 2013

and originally used in the project:

Gabriel Eilertsen, Robert Wanat, Rafal Mantiuk, Jonas Unger: Evaluation of tone mapping operators for HDR-video, In Computer Grahpics Forum Special Issue Proceedings of Pacific Graphics, Singapore, 7-9 October, 2013.

Download HDR-sequence as OpenEXR frames (720p): hallway2.zip (934 MB)
If you wish to use this video sequence in your research, we kindly ask you cite the papers mentioned above.

HDR-video sequence: Water

Tone mapped preview (best viewed in fullscreen)

Online HDR viewer:
Resolution: [High resolution] (7.7 MB), [Low resolution] (2.2 MB),
(Requires a WebGL enabled web browser.)

Sequence information:
This HDR-video sequence captured in the Visual Computing Lab, Norrköping Visualization Centre -C in Sweden using a Nikon f/1.4D 50mm Nikkor lens. The sequence was captured using the methods and algorithms described in:

J. Kronander, S. Gustavson, G. Bonnet, J. Unger: Unified HDR Reconstruction from RAW CFA Data, In proceedings of the International Conference on Computational Photography (ICCP), 2013, Harvard University, Cambridge, USA, April, 2013.

J. Kronander, S. Gustavson, G. Bonnet, A. Ynnerman, J. Unger: A Unified Framework for Multi-Sensor HDR Video Reconstruction, Accepted for publication in Signal Processing: Image Communications, 2013

The images are not calibrated to represent absolute scene luminance measurements.

Download HDR-sequence as OpenEXR frames (720p): water.zip (1.1 GB)
If you wish to use this video sequence in your research, we kindly ask you cite the papers mentioned above.

HDR-video sequence: Norrköping Bridge 2

Tone mapped preview 1 (best viewed in fullscreen)

Tone mapped preview 2 (best viewed in fullscreen)

View a single frame in our online HDR image viewer:
[Full resolution] (7.6 MB), [Low resolution] (971 KB)
(Requires a WebGL enabled web browser.)

Sequence information:
This HDR-video sequence captured in the Visual Computing Lab, Norrköping Visualization Centre -C in Sweden using a Nikon f/1:2.8D 16mm Nikkor lens. The sequence was captured using the methods and algorithms described in:

J. Kronander, S. Gustavson, G. Bonnet, J. Unger: Unified HDR Reconstruction from RAW CFA Data, In proceedings of the International Conference on Computational Photography (ICCP), 2013, Harvard University, Cambridge, USA, April, 2013.

J. Kronander, S. Gustavson, G. Bonnet, A. Ynnerman, J. Unger: A Unified Framework for Multi-Sensor HDR Video Reconstruction, Accepted for publication in Signal Processing: Image Communications, 2013

The images are not calibrated to represent absolute scene luminance measurements.

Download HDR-sequence as OpenEXR frames (720p): bridge2.zip (1.34 GB)
If you wish to use this video sequence in your research, we kindly ask you cite the papers mentioned above.

HDR-video sequence: Norrköping Bridge

Tone mapped preview (best viewed in fullscreen)

View a single frame in our online HDR image viewer:
[Full resolution] (7.6 MB), [Low resolution] (971 KB)
(Requires a WebGL enabled web browser.)

Sequence information:
This HDR-video sequence captured in the Visual Computing Lab, Norrköping Visualization Centre -C in Sweden using a Nikon f/1.4D 50mm Nikkor lens. The sequence was captured using the methods and algorithms described in:

J. Kronander, S. Gustavson, G. Bonnet, J. Unger: Unified HDR Reconstruction from RAW CFA Data, In proceedings of the International Conference on Computational Photography (ICCP), 2013, Harvard University, Cambridge, USA, April, 2013.

J. Kronander, S. Gustavson, G. Bonnet, A. Ynnerman, J. Unger: A Unified Framework for Multi-Sensor HDR Video Reconstruction, Accepted for publication in Signal Processing: Image Communications, 2013

The images are not calibrated to represent absolute scene luminance measurements.

Download HDR-sequence as OpenEXR frames (720p): bridge.zip (1.1 GB)
If you wish to use this video sequence in your research, we kindly ask you cite the papers mentioned above.

HDR-video sequence: C - Exhibition Area

Tone mapped preview (best viewed in fullscreen)

Sequence information:
This HDR-video sequence was captured at Norrköping Visualization Centre in Sweden using a RED EPIC camera set to HDR-X mode. The sequence was radiometrically calibrated using a Photo Research PR-650 photospectrometer. The sequence was originally used in the project:

Gabriel Eilertsen, Robert Wanat, Rafal Mantiuk, Jonas Unger: Evaluation of tone mapping operators for HDR-video, In Computer Grahpics Forum Special Issue Proceedings of Pacific Graphics, Singapore, 7-9 October, 2013.

Download HDR-sequence as OpenEXR frames (720p): exhibition_area.zip (593 MB)
If you wish to use this video sequence in your research, we kindly ask you cite the papers mentioned above.

HDR-video sequence: Norrköping River

Tone mapped preview (best viewed in fullscreen)

View a single fram in our on-line HDR viewer:
Resolution: [High resolution] (8.8 MB), [Low resolution] (2.6 MB),
(Requires a WebGL enabled web browser.)

Sequence information:
This HDR-video sequence was captured outside the Visual Computing Lab, Norrköping Visualization Centre -C in Sweden using a Nikon f/1.4D 50mm Nikkor lens. The sequence was captured using the methods and algorithms described in:

J. Kronander, S. Gustavson, G. Bonnet, J. Unger: Unified HDR Reconstruction from RAW CFA Data, In proceedings of the International Conference on Computational Photography (ICCP), 2013, Harvard University, Cambridge, USA, April, 2013.

J. Kronander, S. Gustavson, G. Bonnet, A. Ynnerman, J. Unger: A Unified Framework for Multi-Sensor HDR Video Reconstruction, Accepted for publication in Signal Processing: Image Communications, 2013

The images are not calibrated to represent absolute scene luminance measurements.

Download HDR-sequence as OpenEXR frames (720p): river.zip (1.18 GB)
If you wish to use this video sequence in your research, we kindly ask you cite the papers mentioned above.

HDR-video light probe data

Each full resolution frame from our HDRv sequences is around 45 MB in size. Therefore, we are currently making sequences donwsampled to 1024x1024 pixels available for download. Full resolution sequences can be made available on request. All sequences are stored as individual OpenEXR frames.
The images are stored in the mirror sphere format, i.e. as the actual image of the light probe sphere.

HDR-video light probe sequence: C

Tone mapped preview (best viewed in full screen)

View a frame on our line HDR viewer:
Resolution: [Medium resolution] (2.4 MB), [Low resolution] (1.5 MB)
(Requires a WebGL enabled web browser.)

Sequence information:
Light probe sequence: captured outside the Norrköping Visualization Center - C in Sweden using a mirror sphere and a Zeiss Makro-Planar T* 100mm f/2 ZF.2 lens. The sequence was captured using the methods and algorithms described in:

J. Kronander, S. Gustavson, G. Bonnet, J. Unger: Unified HDR Reconstruction from RAW CFA Data, In proceedings of the International Conference on Computational Photography (ICCP), 2013, Harvard University, Cambridge, USA, April, 2013.

J. Kronander, S. Gustavson, G. Bonnet, A. Ynnerman, J. Unger: A Unified Framework for Multi-Sensor HDR Video Reconstruction, Accepted for publication in Signal Processing: Image Communications, 2013

The images are not calibrated to represent absolute scene luminance measurements.

Download HDR-sequence as OpenEXR frames (720p): C.zip (1.07 GB)
If you wish to use this video sequence in your research, we kindly ask you cite the papers mentioned above.

HDR-video light probe sequence: Kåkenhus in Norrköping

Tone mapped preview (best viewed in full screen)

Sequence information:
Light probe sequence: captured outside the Norrköping Visualization Center - C in Sweden using a mirror sphere and a Zeiss Makro-Planar T* 100mm f/2 ZF.2 lens. The sequence was captured using the methods and algorithms described in:

J. Kronander, S. Gustavson, G. Bonnet, J. Unger: Unified HDR Reconstruction from RAW CFA Data, In proceedings of the International Conference on Computational Photography (ICCP), 2013, Harvard University, Cambridge, USA, April, 2013.

J. Kronander, S. Gustavson, G. Bonnet, A. Ynnerman, J. Unger: A Unified Framework for Multi-Sensor HDR Video Reconstruction, Accepted for publication in Signal Processing: Image Communications, 2013

The images are not calibrated to represent absolute scene luminance measurements.

Download HDR-sequence as OpenEXR frames (720p): kaken.zip (977 MB)
If you wish to use this video sequence in your research, we kindly ask you cite the papers mentioned above.

Static HDR panoramas and environment images

Here you can find the HDR light probe and background image data captured at a set of different locations. Each image data set contains:

- Two or more high resolution HDR panoramas captured at different positions in the scene.
- A large set of still images (.jpeg) capturing the scene
- For some scenes we have also captured video sequences

Each HDR panorama image is stiched from a set of high resolution HDR image captured using a rotating panorama head. The HDR panoramas are stored using the in OpenEXR image format using the latitude-longitude mapping.
You can either download all images and videos from each location as (large) zip-files or browse individual frames, videos or panoramas in yor web browser.

Location 1, outside the Norrköping Visualization Center - C, Sweden

Data set information:
Capture date: October 2011
Number of HDR panoramas: 2
Number of environment image (.jpeg): 94
The images were captured using a Canon 5D Mark II.