Hugin vs OpenPano
Hugin
hugin.sourceforge.ioOpenPano
github.comSide by side
| Figure | Hugin | OpenPano |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Panorama Stitching Software | 7.8 (#10) | 7.6 (#13) |
| Purpose | Hugin is a cross-platform panoramic imaging toolchain that assembles photographs into immersive panoramas and stitches overlapping pictures. | OpenPano is a C++ program for automatic panorama stitching, written from scratch without computer vision libraries. |
| Windows support | The download page offers a 64-bit Windows installer and says 32-bit Windows is supported only through Hugin 2017.0. | The README cautions that the Windows build process may not work and invites pull requests to improve it. |
Plans
In their own words
Hugin
Hugin is a free, open-source toolchain for stitching overlapping photographs into panoramas, including immersive panoramic images. Its automated Assistant can assemble multi-row photos, while control points support perspective correction. The tutorials also address lens calibration, blend masks, and exposure fusion. Hugin uses Enblend to blend seams and Enfuse to combine bracketed exposures. It supports RAW input, HDR or exposure blending, control-point editing, and batch stitching, and is listed for both panorama types. Hugin runs on Linux, macOS, and Windows. Windows downloads include a 64-bit installer; 32-bit support is limited to versions through Hugin 2017.0. The listed Mac bundle targets macOS 10.9 and newer but does not run on newer arm64 Macs. Linux users can use distribution package managers, Flatpak, or AppImage builds. The project offers a manual, tutorials, FAQs, and the PanoTools wiki, with discussion on its mailing list and bug reports through Launchpad. It is free to use, modify, and share.
OpenPano
OpenPano is a free C++ program for automatic panorama stitching, written from scratch without computer vision libraries. It offers cylinder, camera estimation, and translation modes, each with requirements for image capture or ordering. Its listed techniques include SIFT features, RANSAC-based homography or affine transformations, focal estimation, bundle adjustment, and straightening. The program supports Linux, macOS, and Windows. Build instructions use CMake and make for Linux, macOS, and WSL, and describe a Visual Studio 2015 process for Windows. Eigen and FLANN are build dependencies; libjpeg and CImg are optional image input/output components. The README recommends manually downscaling images of four megapixels or more to save time. Wide-angle images with heavy distortion may not work well unless camera parameters are used to undistort them. Memory use can be large with the default libc allocator; LAZY_READ can reduce it with a minor slowdown. The repository includes an MIT License, which permits use and distribution subject to its conditions and provides the software without warranty.