<![CDATA[Multispectral image is a type of digital image that captures spectral information in several channels or bands. Edge detection is one of the basic techniques in image processing which is used to identify the boundaries of objects in an image. This research aims to analyze the performance of several edge detection algorithms on multispectral images. The algorithms tested include the Sobel, Prewitt, Roberts, Canny, and Laplacian of Gaussian (LoG) algorithms. Tests were carried out on high resolution multispectral images from the Landsat-8 satellite. The evaluation metrics used are accuracy, precision, recall, and F1-score. The research results show that the Canny algorithm has the best performance with the highest F1-score compared to other algorithms. Apart from that, this research also analyzes the effect of the number of channels in multispectral images on the performance of edge detection algorithms.]]>
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