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Shadow Detection and Removal from Remote Sensing Images using NDI and Morphological Operators

by Krishna Kant Singh, Kirat Pal, M. J. Nigam
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 42 - Number 10
Year of Publication: 2012
Authors: Krishna Kant Singh, Kirat Pal, M. J. Nigam
10.5120/5732-7805

Krishna Kant Singh, Kirat Pal, M. J. Nigam . Shadow Detection and Removal from Remote Sensing Images using NDI and Morphological Operators. International Journal of Computer Applications. 42, 10 ( March 2012), 37-40. DOI=10.5120/5732-7805

@article{ 10.5120/5732-7805,
author = { Krishna Kant Singh, Kirat Pal, M. J. Nigam },
title = { Shadow Detection and Removal from Remote Sensing Images using NDI and Morphological Operators },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 42 },
number = { 10 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 37-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume42/number10/5732-7805/ },
doi = { 10.5120/5732-7805 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:31:01.058990+05:30
%A Krishna Kant Singh
%A Kirat Pal
%A M. J. Nigam
%T Shadow Detection and Removal from Remote Sensing Images using NDI and Morphological Operators
%J International Journal of Computer Applications
%@ 0975-8887
%V 42
%N 10
%P 37-40
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Shadows appear in remote sensing images due to elevated objects. Shadows cause hindrance to correct feature extraction of image features like buildings, towers etc. in urban areas it may also cause false color tone and shape distortion of objects, which degrades the quality of images. Hence, it is important to segment shadow regions and restore their information for image interpretation. This paper presents an efficient and simple approach for shadow detection and removal based on HSV color model in complex urban color remote sensing images for solving problems caused by shadows. In the proposed method shadows are detected using normalized difference index and subsequent thresholding based on Otsu's method. Once the shadows are detected they are classified and a non shadow area around each shadow termed as buffer area is estimated using morphological operators. The mean and variance of these buffer areas are used to compensate the shadow regions.

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Index Terms

Computer Science
Information Sciences

Keywords

Shadow Compensation Shadow Detection Thresholding

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