Information states in radar imagery of sea ice

It is shown empirically that information in an image of sea ice exists in two forms-textural and structural. It is shown that such information can be extracted from the conditional probability of intensity differences between neighboring pixels. There exists a relationship between the two forms of information, called the information curve, which has identifiable subsections, each related to an ice type. The overall state of the sea ice image, composed as it is of a mixture of ice types, can therefore be given by the location of phase transition points that mark the end points of the subsections on the information curve composed of the two types of information. This result leads to a segmentation of the image by ice type, The properties of the information within the image are examined, It is shown that the textural information associated with individual ice pieces is scale invariant, whereas the structural information associated with the size and shape of these pieces, which dominates the image, has a scaling or fractal property. These results led to the examination of similarity sets, describing scaled intensity differences and separation jointly. Significantly, a multifractal relationship for these sets holds at all intensities, at least for ice types associated with brittle fracture. Another result inspired by the need to identify paths of least resistance through an ice field is the existence of a distinct change in the connectivity of these similarity sets at a critical value of the index parameter of the set, Such a critical value is in turn related to that of the local textural information, which is related to the phase transitions associated with the relationship between textural and structural information, It is shown that there exists an intimate relationship between scaling and connectivity of local trees that has application both in defining paths and identifying ice type.