Hyperspectral edge filtering for measuring homogeneity of surface cover types

Abstract

Edge operators are widely used on grey-level images as a first step in image segmentation or image interpretation. Methods that are currently used for edge filtering are complex and only valid under certain conditions, or useful for three-band colour images only. The problem remains on how to apply edge filtering on multispectral or even hyperspectral images. This paper presents a method that can be used for multispectral and hyperspectral edge filtering. The method uses filtering techniques in combination with three distance measures, namely the Euclidean distance, the spectrum intensity difference, or the spectral angle. The same hyperspectral edge filters serve as homogeneity measures. By simply ‘plugging in’ another distance measure in the same filter, a separation between intensity and spectral content is achieved, which makes the hyperspectral edge filters the natural extension of colour edge filters. The hyperspectral edge filters use information from all spectral bands to arrive at a (dis)similarity map in one step. The edge filters were tested on HyMap hyperspectral imagery of the island of Schiermonnikoog. The test area includes agriculture and a saltmarsh. Experimental results are presented. The spectral angle (dis)similarity of neighbouring pixels can be directly compared with spectral angles already obtained by using the Spectral Angle Mapper for classification. We show that these hyperspectral edge filters assist image interpretation, even in heterogeneous ecosystems such as saltmarshes.