Statistical dependence between orientation filter outputs used in a human-vision-based image code

We present an image coding scheme based on the properties of the early stages of the human visual system. The image signal is decomposed via even and odd symmetric, frequency and orientation selective band-pass filters in analogy to the quadrature phase simple cell pairs in the visual cortex. The resulting analytic signal is transformed into a local amplitude and local phase representation in order to achieve a better match to its signal statistics. Both intra filter dependencies of the analytic signal and inter filter dependencies between different orientation filters are exploited by a suitable vector quantization scheme. Inter orientation filter dependencies are demonstrated by means of a statistical evaluation of the multidimensional probability density function. The results can be seen as an empirical confirmation of the suitability of vector quantization in subband coding. Instead of generating a code book by use of an conventional design-algorithm, we suggest a feature specific partitioning of the multidimensional signal space matched to the properties of human vision. Using this coding scheme satisfactory image quality can be obtained with about 0.78 bit/pixel.