EVALUATION OF LINEAMENT DETECTION ALGORITHMS 
USING MULTI-BAND REMOTE SENSING IMAGES 
Jinfei Wang 
Associate Professor 
Department of Geography, University of Windsor 
Windsor, Ontario, Canada 
Commission VII, Working Group 4 
KEYWORDS: Geology, Algorithms, Landsat, Feature identification algorithms, Geologic lineaments. 
ABSTRACT 
This paper presents a lineament detection method using multi-band remote sensing images. A Linear 
feature Network Detection and Analysis system - LINDA has been applied to multispectral satellite data 
such as Landsat TM images in the Canadian shield area of northern Ontario. The proposed technique 
involves the following steps: 
Transform. 
Preprocessing, Edge detection, Multi-band combination and Hough 
The results demonstrate that the proposed multi-band lineament detection procedure 
achieves better performance in comparison with the existing single-band algorithms. 
INTRODUCTION 
Lineaments are linear topographical or tonal 
features on the terrain representing zones of 
structural weakness (Williams, 1983). They 
may be recognized on and interpreted from 
images and maps. Identification and mapping of 
lineaments from satellite images is an important 
use of remote sensing data in many geologic 
applications. On satellite images, lineaments 
usually appear as straight lines or edges, but 
frequently a lineament may have gaps in it due to 
poor contrast of the lineament with its 
surroundings or coverage of surface materials. 
In visual interpretation and mapping of 
lineaments, geologists use their knowledge and 
experience to connect lines and edges which are 
collinear and broken into a series of segments. It 
is suggested that some of the "rules" that are 
used by geologists in their image interpretation 
can be applied in automated lineament extraction 
from digital imagery. This paper presents a 
lineament detection method using multi-band 
remote sensing images. A Linear feature 
Network Detection and Analysis system - LINDA 
(Wang, 1993) has been applied to multispectral 
satellite data such as Landsat TM images in the 
Canadian shield area of northern Ontario. 
750 
METHODOLOGY 
The proposed technique involves the following 
steps: 
Preprocessing 
For the majority of images, it is important to 
apply a filter to the image to smooth it and 
remove most of the noise. If this were not done, 
problems of isolating individual lineaments would 
occur later in the analysis. In this study, a 
median filter was applied to the original data. 
Multi-band combination 
As opposed to most existing lineament detection 
methods, which use single-band images only, the 
proposed method is designed to operate on 
several channels and combine different linear 
feature information. Principal Component 
Analysis (PCA), band ratioing, and their 
combination are applied to the filtered channels. 
The resultant channel contains edge information 
from multiple original channels. 
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B7. Vienna 1996 
(Ty. OY "Irs 85 °° MN m 
nN C* 
—