Image coding for storage and transmission based on morphological segmentation

The objective of the paper is to present a new object based image coding technique using morphological segmentation. These are the first results of a final objective of proposing a completely new coding/decoding scheme for storage and transmission applications based on Mathematical Morphology. The paper presents a new object based image coding algorithm that involves three main processing steps: segmentation, coding of contours and coding of the inside. The three fundamental coding steps of our approach work on a multiscale representation of the data. The coding of contours represents the shape and location of the region and is based on techniques relying on chain codes. The coding of inside consists in modeling the gray level function of the image and in filling each region with this model. Orthogonal polynomials are used for inside coding and bit allocation techniques are developed such that efficient compression rates are obtained. Several computer generated images are presented that show good visual results for a variety of different compression ratios. The techniques can also be applied to image sequences. Current research is under way to propose new coding techniques for both the contour and the inside coding using Mathematical Morphology.