Region-based image coding using polynomial intensity functions

The vast majority of coded images are real-world images. These images consist of distinct objects within a scene, where each object has its own reflective, textural and lighting characteristics. Region-based image coding encodes these images by partitioning the scene into objects, and then describing each object´s characteristics using a set of parameters. The paper uses orthonormal polynomial functions to describe the lighting and reflective characteristics of each object. The coefficients of these polynomials are coded with linear quantisers that have their decision boundaries spaced according to rate-distortion considerations. The textural component of each object is coded using vector quantisation of the autocorrelation coefficients of the residual. The partitioning of the image into distinct objects is achieved with a segmentation algorithm which attempts to maximise the rate-distortion performance of the encoding procedure as a whole. In doing so, the segmentation algorithm partitions the image into distinct objects as well as providing estimates for the optimal bit allocations among the polynomial coefficients. Results generated by this method show reconstructions with quality superior to other region-based methods, both objectively and subjectively