As part of the physically based recognition approach, new concepts and algorithms for shape from multiple views and multiple cues are being developed. In recent years, arithmetic coding has gained considerable attention and is nowadays generally accepted as a standard for lossless compression. The majority of image data compression procedures view the data stream as a one-dimensional finite context Markov chain. In order to model digital images, their two-dimensional structure should be reflected in the data structure as well as in the order of processing. The objective of this project is to investigate two-dimensional and hierarchical higher order Markov chains and to implement corresponding probabilistic models for lossless image compression based on the technique of arithmetic coding.
First results are available.
They show better compression performance than Ziv-Lempel anf lossless JPEG procedures. Motion pictures recorded on chemical film represent an important cultural heritage. These images are, however, often badly damaged. In multimedia system platforms of the future, high resolution moving images will be scanned, digitized, processed and reproduced. The aim of this study is to understand the requirements for digitally removing image artefacts typical for damaged motion pictures.