Textural Analysis And Real-Time Classification of Sea-Ice Types Using Digital SAR Data

Abstract

Digital measures of synthetic-aperture radar (SAR) image texture, as well as the local approximation to the mean value of individual ice types, were used to perform discrimination and mapping of ice types. The SAR data described in this paper were gathered in March, 1979, over the Beaufort Sea as part of the Canadian SURSAT project. Digital SAR data from a 3 × 3 km area were obtained using optical processing of the signal film and digital recording of the output image. Prior to performing the textural analysis, a digital filter algorithm was developed that minimizes the effect of radar-system-generated coherent speckle and produces an image approximating local tone while preserving edge definition. This image was used in the analysis to separate image tone from image texture. The textural analysis, which included calculating the entropy and inertia of the image, indicated that first- and multiyear, smooth- and rough-ice types could be distinguished based on the textural values obtained from the data with an overall accuracy of 65 percent. This study has also considered the use of cellular operations based upon neighborhood transformations to calculate the textural values. This computation method can potentially reduce the time to compute textural features on a general-purpose computer to near real-time rates.