Filtering of ASTER digital elevation models using mathematical morphology

Abstract

This paper presents results of research undertaken on the creation and filtering of digital elevation models (DEMs) from a stereo pair of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images. The raw DEM, created by automatic image matching, appears to be very noisy. Two types of irregularities can be observed. First, a random occurrence of small sinks and mounds with high amplitude is observed. Secondly, a more regular east–west-oriented pattern of noise is present. Many DEM-creation programs provide some editing tools to smooth out the irregularities, including some noise removal, smoothing and interpolation algorithms. However, the application of these algorithms has an important impact on the values of the parameters derived from the elevation, such as slope, aspect and curvature. In this study we propose a filtering algorithm based on morphological greyscale reconstruction in order to remove the sinks and mounds. This technique is very effective in mitigating the artefacts while preserving the remaining structures. For the regular pattern, a linear north–south-oriented low-pass filtering showed the best results. This approach was compared with a median filter and proved to be more effective in terms of both elevation and slope parameters.

Extracting Ground-Level DEM From SRTM DEM in Forest Environments Based on Mathematical Morphology

“…In a morphological operation, the value of each pixel in the output image is based on a comparison of the corresponding pixel in the input image with its neighbors. Mathematical morphology has been used for the analysis of DEMs, which are regarded as a grayscale image with the gray level of a pixel standing for its elevation above the base plane [12], [13], [15].…”

“…In particular, by changing the filter window size and using elevation difference thresholds, nonground features with different sizes can be effectively removed [11]. In addition, morphology-based approaches have been also used for basin delineation from DEMs [12], peaks and pits reconstruction from DEMs [13], and outlier elimination from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEMs [14], [15], etc. These studies inspired us to apply mathematical morphology to the SRTM DEM for deriving the GLD.…”