Evaluation of selected edge detection techniques in remotely sensed images

Konstantinos G. Karantzalos; Demetre P. Argialas

doi:10.1117/12.463519

13 March 2003 Evaluation of selected edge detection techniques in remotely sensing images

Konstantinos G. Karantzalos, Demetre P. Argialas

Proceedings Volume 4885, Image and Signal Processing for Remote Sensing VIII; (2003) https://doi.org/10.1117/12.463519
Event: International Symposium on Remote Sensing, 2002, Crete, Greece

Abstract

This paper describes the experience gained from the evaluation of selected automatic edge detection techniques applied to LANDSAT TM, SPOT HRV, IRS 1C and IKONOS images. Emphasis was given to the detection of man-made objects and linear features such as coastlines, roads and parcel boundaries in combination with selected preprocessing and postprocessing operations. As preprocessing Gaussian, adaptive and morphological operators were implemented and tested for image enhancement and smoothing. Edge extraction processing followed. First the Canny edge detector was applied. Then a morphological nonlinear Laplacian operator was applied and its zero-crossings yielded edge locations. Finally an edge detector resulting by overlaying two thresholded images from the Prewitt gradient, preserving edges appearing in both images, was applied. Postprocessing followed to eliminate noisy edges and restore edge connectivity through morphological operators. An analysis of the relative performance of the processing scheme indicated each detector's relation to noise (features at certain undesired scales, shadows along roads boundaries, irrelevant edges within parcel boundaries) and the set of specific parameters needed for proper enhancement and smoothing before edge extraction.

Citation Download Citation

Konstantinos G. Karantzalos and Demetre P. Argialas "Evaluation of selected edge detection techniques in remotely sensing images", Proc. SPIE 4885, Image and Signal Processing for Remote Sensing VIII, (13 March 2003); https://doi.org/10.1117/12.463519

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