Pattern colour separable image coding for content based indexing
A colour image coding system based on the pattern colour separable (PCS) theory of human colour vision is developed. The PCS image coding system codes an image using three separate channels: pattern, colour and strength. The pattern channel corresponds to the visual pathway that is sensitive to spatial frequency information, the colour channel corresponds to the visual pathway that is sensitive to the colour information and the strength channel corresponds to the visual pathway that is sensitive to the strength of the visual stimulus. Decoding of the image is based on a neural network trained in a self-organizing manner. Compression performances of the system are shown to be very good. Query by image contents is a successful approach to image database indexing and retrieval. Because image data take up huge amount of storage space and network bandwidth, compressing the image is a standard practice. Given that images are compressed/coded in a database, it mould be more efficient if the compressed data can also be directly used as indices for content-based query. We show that the contents (shapes and colours) of the images are embedded in the compressed data of the PCS system and therefore can be readily and efficiently used as indices for content based image indexing.