COMPARISON OF IMAGE ENHANCEMENT TECHNIQUES FOR RAPID PROCESSING OF POST FLOOD IMAGES

COMPARISON OF IMAGE ENHANCEMENT TECHNIQUES FOR RAPID PROCESSING OF POST FLOOD IMAGES

Satellite images are widely used for assessing the areal extent of flooded areas. However, presence of clouds and shadow limit the utility of these images. Numerous digital algorithms are available for enhancing such images and highlighting areas of interest. These algorithms range from simple to co...

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Bibliographic Details
Published in:International archives of the photogrammetry, remote sensing and spatial information sciences. Vol. XLIV-M-2-2020; pp. 45 - 50
Main Authors: Harichandana, M., Sowmya, V., Sajithvariyar, V. V., Sivanpillai, R.
Format: Journal Article Conference Proceeding
Language:English
Published: Gottingen Copernicus GmbH 2020
Copernicus Publications
Subjects:
Algorithms
Clouds
Digital imaging
Disaster management
Equalization
Floods
Histograms
Image contrast
Image enhancement
Image quality
Satellite imagery
Shadows
Spaceborne remote sensing
Online Access:Get full text
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Summary:Satellite images are widely used for assessing the areal extent of flooded areas. However, presence of clouds and shadow limit the utility of these images. Numerous digital algorithms are available for enhancing such images and highlighting areas of interest. These algorithms range from simple to complex, and the time required to process these images also varies considerably. For disaster response, it is important to select an algorithm that can enhance the quality of the images in relatively short time. This study compared the relative performance of five traditional (Histogram Equalization, Local Histogram Equalization, Contrast Limited Adaptive Histogram Equalization, Gamma Correction, and Linear Contrast Stretch) algorithms for enhancing post-flood satellite images. Flood images with different levels of clouds and shadows were enhanced and output generated were evaluated in terms of processing time and quality as measured by Blind/Reference less Image Spatial Quality Evaluator (BRISQUE), a no-reference image quality metric. Findings from this study will provide valuable information to image analysts for selecting a suitable algorithm for rapidly processing post-flood satellite images.
ISSN:2194-9034
1682-1750
2194-9034
DOI:10.5194/isprs-archives-XLIV-M-2-2020-45-2020