FCC develops image analysis methods for automated quantitative analysis and enhancement of images and videos. Example applications are automated tracking of cells or particles in time-lapse sequences in fluorescence bioimaging and enhancement and display of low light videos for the automotive industry.
Observation of a scene and imaging of the same scene are usually strikingly different. For example, the high dynamic range needed to observe details in deep shadows as well as in direct sunlight is typically impossible to capture and depict on an ordinary display without some kind of processing of the image. FCC investigates, develops and benchmarks algorithms for the enhanced display of images and videos with applications towards the automotive industry and in particular car safety. Here, the videos are typically degraded by noise as well as subject to poor or non-uniform illumination. Unprocessed and displayed on a common display with low dynamic range without the use of any kind of tone mapping, the visual quality becomes very low, making it difficult for a person to perceive the observed scene and to suitably react to possible safety threats.
Our goal is to provide mathematical and statistical tools to application fields that produce images where quantitative measurements can, or could be, conducted.
Quantitative bioimaging has in the last couple of years aroused substantial interest for life science applications. In eukaryotic cells, quantitative measurements of protein expression, protein localization and protein-protein interactions are key components for a proper understanding of cell functionality. Fluorescence microscopy and the use of fluorescent protein tags, which facilitates specific labeling of proteins, enables studies of protein expression over generations and large populations. However, since human interpretation of images is qualitative and subjective, software for objective automatic image analysis is necessary for standardized measurements, in particular for high-throughput studies. Quantitative bioimaging is also an excellent setup for generating high quality data needed for modeling and understanding the complex processes involved in systems biology.