Inhaltsbereich
Publications
Abstract (EDOC: 15536)
Active contours, or snakes, are broadly used to detect linear features such
as edges. However, they are often restricted in the delineation of regions
of interest within the hyperspectral domain. In this paper, a new approach
is presented, referred to as “Busyness Multiple Correlation Edge Detector”,
that enables hyperspectral boundary detection using active contours such as
“Alternating Vector Field Convolution” snakes. The combination of
“Alternating Vector Field Convolution” snakes with the “Busyness Multiple
Correlation Edge Detector” opens a broad set of applications by concurrent
high convergence quality and speed. Furthermore, specific snake
initialisations are tested. A series of examples are used to both
demonstrate the approach and underline the benefits of the new methods.
(2010): Hyperspectral boundary detection based on the Busyness Multiple Correlation Edge Detector and Alternating Vector Field Convolution snakes. ISPRS Journal of Photogrammetry and Remote Sensing, 65, 5, 468-478.
(2010): Hyperspectral boundary detection based on the Busyness Multiple Correlation Edge Detector and Alternating Vector Field Convolution snakes. ISPRS Journal of Photogrammetry and Remote Sensing, 65, 5, 468-478.

