A Novel Method to Detect Shadows on Multispectral Images

Date

2016-09-28

Author

Sevim, Hazan Daglayan
Çetin, Yasemin
Baskurt, Didem Ozisik

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

141
views

0
downloads

Shadowing occurs when the direct light coming from a light source is obstructed by high human made structures, mountains or clouds. Since shadow regions are illuminated only by scattered light, true spectral properties of the objects are not observed in such regions. Therefore, many object classification and change detection problems utilize shadow detection as a preprocessing step. Besides, shadows are useful for obtaining 3D information of the objects such as estimating the height of buildings. With pervasiveness of remote sensing images, shadow detection is ever more important. This study aims to develop a shadow detection method on multispectral images based on the transformation of C-1 C-2 C-3 space and contribution of NIR bands. The proposed method is tested on Worldview-2 images covering Ankara, Turkey at different times. The new index is used on these 8-band multispectral images with two NIR bands. The method is compared with methods in the literature.

Subject Keywords

Multispectral Images, Worldview-2, Shadow Detection, Remote Sensing

URI

https://hdl.handle.net/11511/56340

DOI

https://doi.org/10.1117/12.2241938

Conference Name

Conference on Image and Signal Processing for Remote Sensing XXII

Collections

Graduate School of Informatics, Conference / Seminar

Suggestions

OpenMETU
Core

A Cloud Removal Algorithm to Generate Cloud and Cloud Shadow Free Images Using Information Cloning Kalkan, Kaan; Maktav, M. Derya (Springer Science and Business Media LLC, 2018-08-01) One of the main problems of optical remote sensing is clouds and cloud shadows caused by specific atmospheric conditions during data acquisition. These features limit the usage of acquired images and increase the difficulty in data analysis, such as normalized difference vegetation index values, misclassification, and atmospheric correction. Accurate detection and reliable cloning of cloud and cloud shadow features in satellite images are very useful processes for optical remote sensing applications. In thi...
A NOVEL SHADOW RESTORATION ALGORITHM BASED ON ATMOSPHERIC EFFECTS FOR AERIAL IMAGES Aytekin, Caglar; Alatan, Abdullah Aydın (2010-09-29) In aerial images, the performance of the segmentation and object recognition algorithms could suffer due to shadows in the scene. This effort describes a novel shadow restoration algorithm based on atmospheric effects and characteristics of sun light for aerial images. Firstly, shadow regions are detected exploiting the Rayleigh scattering phenomena and the well-known fact related to the low illumination intensity in the shadow regions. After detection, shadow restoration is achieved by first restoring part...
Utilization of False Color Images in Shadow Detection Aksoy, Yagiz; Alatan, Abdullah Aydın (2012-10-13) Shadows are illuminated as a result of Rayleigh scattering phenomenon, which happens to be more effective for small wavelengths of light. We propose utilization of false color images for shadow detection, since the transformation eliminates high frequency blue component and introduces low frequency near-infrared channel. Effectiveness of the approach is tested by using several shadow-variant texture and colorrelated cues proposed in the literature. Performances of these cues in regular and false color image...
Shadow detection on multispectral images Dağlayan Sevim, Hazan; Çetin, Yasemin; Department of Information Systems (2015) Shadows caused by clouds, mountains or high human-made structures pose challenges for identiﬁcation of objects from satellite or aerial images since they deteriorate and mask true spectral properties of the objects. Therefore, they should be detected to accurately classify objects. Moreover, in change detection problems, shadows deteriorate performance because mere spectral changes act as actual object changes. Shadows are also useful as cues for estimating the height of an object or determining the time of...
A fuzzy neural network model to forecast the percent cloud coverage and cloud top temperature maps Tulunay, Y.; Şenalp, E. T.; Öz, Ş.; Dorman, L. I.; Tulunay, E.; Menteş, S. S.; Akcan, M. E. (Copernicus GmbH, 2008-12-5) Atmospheric processes are highly nonlinear. A small group at the METU in Ankara has been working on a fuzzy data driven generic model of nonlinear processes. The model developed is called the Middle East Technical University Fuzzy Neural Network Model (METU-FNNM). The METU-FNN-M consists of a Fuzzy Inference System (METU-FIS), a data driven Neural Network module (METU-FNN) of one hidden layer and several neurons, and a mapping module, which employs the Bezier Surface Mapping technique. In this paper, t...

Citation Formats

H. D. Sevim, Y. Çetin, and D. O. Baskurt, “A Novel Method to Detect Shadows on Multispectral Images,” Edinburgh, SCOTLAND, 2016, vol. 10004, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/56340.