Multi-dimensional edge detection operators

Sungwook Youn; Chulhee Lee

doi:10.1117/12.2052684

22 May 2014 Multi-dimensional edge detection operators

Sungwook Youn, Chulhee Lee

Proceedings Volume 9124, Satellite Data Compression, Communications, and Processing X; 912407 (2014) https://doi.org/10.1117/12.2052684
Event: SPIE Sensing Technology + Applications, 2014, Baltimore, MD, United States

Abstract

In remote sensing, modern sensors produce multi-dimensional images. For example, hyperspectral images contain hundreds of spectral images. In many image processing applications, segmentation is an important step. Traditionally, most image segmentation and edge detection methods have been developed for one-dimensional images. For multidimensional images, the output images of spectral band images are typically combined under certain rules or using decision fusions. In this paper, we proposed a new edge detection algorithm for multi-dimensional images using secondorder statistics. First, we reduce the dimension of input images using the principal component analysis. Then we applied multi-dimensional edge detection operators that utilize second-order statistics. Experimental results show promising results compared to conventional one-dimensional edge detectors such as Sobel filter.

Citation Download Citation

Sungwook Youn and Chulhee Lee "Multi-dimensional edge detection operators", Proc. SPIE 9124, Satellite Data Compression, Communications, and Processing X, 912407 (22 May 2014); https://doi.org/10.1117/12.2052684

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