To apply for this task please complete this mandatory coding challenge together with your application: T872
Applications without matching coding challenge completed will not be considered.
Open Cine Overview: https://www.apertus.org/opencine
Open Cine Github Repo: https://github.com/apertus-open-source-cinema/opencine/tree/master
**Goal:** Implement different de-Bayering algorithms, e.g. nearest neighbor, linear (already exists as prototype, but still not added to OC core module), green edge directed or use 3rd party library which is still maintained and has clear API (preferably C++11, instead of plain old C). This would allow to show the user a preview of recorded material and let them adjust some parameters to check the quality. Next step would be to accelerate the implementation by using multi-threading if not already done or OpenCL on CPU/GPU.
This creates the foundation to test raw footage with various debayering methods and compare their quality/issues to each other. Also it allows us to analyse the different requirements for the debayering process depending on raw footage being recorded with or without an optical low pass filter.
-- VisualStudio 2015
-- Qt 5.7
-- optionally: GUI client for Git (e.g. GitKraken or SourceTree)
- **Linux** (e.g. LinuxMint 18.1)
-- Qt 5.7
-- OpenGL headers from freeglut3-dev package
-- optionally: GUI client for Git (e.g. GitKraken)
**Required programming skills:**
- C++ or similar language experience
- Basic understanding of image processing
**Difficulty level:** Medium
**Mentors:** Andrej, Alex