NDLI: Edge detection based on the Shannon Entropy by piecewise thresholding on remote sensing images

Content Provider	IET Digital Library
Author	Kiani, Abbas Sahebi, Mahmod Reza
Abstract	Edge detection is one of the most important concepts used in processing of remote sensing images. The aim of edge detection is to mark the points of an image at which the rate of brightness changes sharply. Sharp changes in image features often represent important events and changes in environmental properties. In other words, edges can be defined as the boundary between two regions separated by two relatively distinct grey level properties. Most classic mathematical methods for edge detection are based on deriving original image pixels such as Laplacian gradient operator. In remote sensing images, because of the high variation rate, the edge detection operators may have some weaknesses in correct detection of the scope of complications. This study provides a novel approach for detecting the edges based on the features of remote sensing images. In this method, at first, thresholds of different regions of the image were determined in a piecewise manner; then, by using the proposed methods, appropriate thresholds were extracted, and finally, the boundary between these regions was extracted using Shannon entropy. The obtained results were compared with some standard algorithms and it was observed that the method was efficiently able to detect edges.
Starting Page	758
Ending Page	768
Page Count	11
ISSN	17519632
Volume Number	9
e-ISSN	17519640
Issue Number	Issue 5, Oct (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/9/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2013.0192
Journal	IET Computer Vision
Publisher Date	2015-04-24
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Computer Vision And Image Processing Technique Data And Information; Acquisition, Processing, Storage And Dissemination in Geophysics Edge Detection Edge Detection Operators Environmental Property Geophysical Image Processing Geophysical Technique And Equipment Geophysics Computing Gradient Method Grey Level Property Image Pixel Information Theory Instrumentation And Technique For Geophysical, Hydrospheric And Lower Atmosphere Research Laplacian Gradient Operator Mathematical Analysis Mathematical Method Optical, Image And Video Signal Processing Optimisation Technique Piecewise Thresholding Remote Sensing Remote Sensing Image Shannon Entropy Sharp Changes
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A robust ragged cloud detection algorithm for remote sensing image

Superpixel segmentation and machine learning classification algorithm for cloud detection in remote-sensing images

Object-based method for optical and SAR images change detection

Improved fast mean shift algorithm for remote sensing image segmentation

Hierarchical detection method of specific artificial region using local structural constraint in remote sensing images

Patch-Based Dark Channel Prior Dehazing for RS Multi-spectral Image

Composite kernels conditional random fields for remote-sensing image classification

Kernel spectral angle mapper

Pansharpening with transform-based gradient transferring model

Edge detection based on the Shannon Entropy by piecewise thresholding on remote sensing images

Similar Documents

A robust ragged cloud detection algorithm for remote sensing image

Superpixel segmentation and machine learning classification algorithm for cloud detection in remote-sensing images

Object-based method for optical and SAR images change detection

Improved fast mean shift algorithm for remote sensing image segmentation

Hierarchical detection method of specific artificial region using local structural constraint in remote sensing images

Patch-Based Dark Channel Prior Dehazing for RS Multi-spectral Image

Composite kernels conditional random fields for remote-sensing image classification

Kernel spectral angle mapper

Pansharpening with transform-based gradient transferring model

Edge detection based on the Shannon Entropy by piecewise thresholding on remote sensing images