NDLI: Salient Remote Sensing Image Segmentation Based on Rate-Distortion Measure

Content Provider	IEEE Xplore Digital Library
Author	Faur, D. Gavat, I. Datcu, M.
Copyright Year	2004
Abstract	The ill-defined nature of the segmentation problem makes the selection of the optimal image partition difficult. One can characterize image segmentation as an attempt to find the best possible representation of a data set using a certain number of ldquoobjects.rdquo This can be regarded as data information compression, resulting in the distortion of the original values. Data sets are well represented when the correct number of regions is chosen. The concept behind this approach is similar to the main problem of rate distortion theory: A finite set of code words is chosen to approximate the numbers or source symbols as well as possible. In our approach, the number of regions is equivalent to the number of code words. The mean of a region provides canonical representation of respective group members, and the distortion function is the mean-square error assuring a good evaluation method for image segmentation.
Sponsorship	IEEE Geoscience and Remote Sensing Society
Starting Page	855
Ending Page	859
Page Count	5
File Size	688711
File Format	PDF
ISSN	1545598X
Volume Number	6
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Remote sensing Image segmentation Rate-distortion Image coding Rate distortion theory Data compression Information technology Pixel Image color analysis Image texture analysis segmentation Information compression rate distortion theory
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Geotechnical Engineering and Engineering Geology

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 Spatially-Constrained Color–Texture Model for Hierarchical VHR Image Segmentation

Segmentation of Remote Sensing Images Using Similarity-Measure-Based Fusion-MRF Model

Visual Distortion Sensitivity Modeling for Spatially Adaptive Quantization in Remote Sensing Image Compression

New Rate Distortion Bounds for Natural Videos Based on a Texture-Dependent Correlation Model

Supervised Segmentation of Remote Sensing Image Using Reference Descriptor

Infornation Content Analysis of Landsat Image Data for Compression

Region Based Rate-Distortion Analysis for 3D Video Coding

Anomaly-Based JPEG2000 Compression of Hyperspectral Imagery

Hierarchical Texture-Based Segmentation of Multiresolution Remote-Sensing Images

Salient Remote Sensing Image Segmentation Based on Rate-Distortion Measure

Similar Documents

A Spatially-Constrained Color–Texture Model for Hierarchical VHR Image Segmentation

Segmentation of Remote Sensing Images Using Similarity-Measure-Based Fusion-MRF Model

Visual Distortion Sensitivity Modeling for Spatially Adaptive Quantization in Remote Sensing Image Compression

New Rate Distortion Bounds for Natural Videos Based on a Texture-Dependent Correlation Model

Supervised Segmentation of Remote Sensing Image Using Reference Descriptor

Infornation Content Analysis of Landsat Image Data for Compression

Region Based Rate-Distortion Analysis for 3D Video Coding

Anomaly-Based JPEG2000 Compression of Hyperspectral Imagery

Hierarchical Texture-Based Segmentation of Multiresolution Remote-Sensing Images

Salient Remote Sensing Image Segmentation Based on Rate-Distortion Measure