Besides my research in computer vision related tasks such as optical flow, photometric stereo, and shape matching and my focus on PDE-based compression, I have also ventured in other image processing tasks. One of these tasks was mathematical morphology. We developed a partial differential equation based leveling model and used a bi-cone shaped colour space to filter our texture in images. In contrast to classical levelling approaches our method also works for well for colour images. The results were published at the ISMM 2017.
Another topic that I shortly worked on was optimized anisotropic Poisson denoising method which we successfully applied on electron microscopy images.
The source code for the PDE-based matrix valued colour levelling is available as a zip archive. The code is written in Matlab and released under a GPLv3 or later licence. This code is not maintained anymore.
Also, over the years I’ve implemented quite a few image processing algorithms in Matlab and Mathematica: here and here. This code is also released under a GPLv3 or later licence. Please note that, as mentioned here and here that the code is completely unmaintained and probably won’t work out of the box.