Summary form only given. The ability of the human visual system to perceive colors as approximately constant irrespective of the illuminant is called color constancy. The output of a sensor varies with the type of illuminant used and is therefore not color constant. Color constancy algorithms try to compute a color constant descriptor from the measured data (M. Ebner, 2007). We show how color constancy can be implemented within JPEG and JPEG2000 by an adaptation of the well-known Retinex algorithm (E.H. Land and J.J. McCann, 1971), (E.H. Land, 1980). Compared to the normal decoding processes only little additional overhead is introduced into the processing pipeline.

The human visual system is able to perceive colors as approximately constant. This ability is known as color constancy. In contrast, the colors measured by a sensor vary with the type of illuminant used. Color constancy is very important for digital photography and automatic color-based object recognition. In digital photography, this ability is known under the name automatic white balance. A number of algorithms have been developed for color constancy. We review two well-known color constancy algorithms, the gray world assumption and the Retinex algorithm and show how a color constancy algorithm may be integrated into the JPEG2000 framework. Since computer images are usually stored in compressed form anyway, little overhead is required to add color constancy into the processing pipeline.

Evolutionary algorithms apply the processes of variation, reproduction and selection to look for an individual that is capable of solving the task in hand. In order to improve the evolvability of a population, we propose to copy important characteristics of nature's search space. Desired characteristics for a genotype-phenotype mapping are described, and several highly redundant genotype-phenotype mappings are analyzed in the context of a population-based search. We show that evolvability is influenced by the existence of neutral networks in the genotype space. The extent of the neutral networks affects the interconnectivity of the search space and thereby affects evolvability. Species evolving on a non-redundant mapping reach a state of stasis after a few generations; in effect, evolution comes to a halt. However, species evolving on a genotype-phenotype mapping with extensive neutral networks are continuously able to find adaptive mutations and are able to locate higher optima. The existence of highly intertwined neutral networks increases the evolvability of a population.

Weighted finite automata (WFA) exploit self-similarities within single pictures and also sequences of pictures to remove spatial and temporal redundancies. Their implementation then combines techniques from hierarchical methods related to quadtrees and from vector quantization to achieve performance results for low bit rates which can be put on a par with state-of-the-art codecs like embedded zero-tree wavelet coding. Due to their simple mathematical structure, WFA provide an ideal platform for efficient hybrid compression methods. Therefore, WFA were chosen as a starting point for a fractal-like video compression integrating a hierarchical motion compensation as well as an option to vary the compression quality between "centers of interest" and "background" in a flexible manner.