Improving pixel based change detection accuracy using an object-based approach in multitemporal sar flood images

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Logic Mind Technologies
Vijayangar (Near Maruthi Medicals), Bangalore-40
Ph: 8123668124 // 8123668066
Title: Improving Pixel-Based Change Detection
Accuracy Using an Object-Based Approach in
Multitemporal SAR Flood Images
Abstract—Most of existing change detection methods could be classified into three
groups, the traditional pixel-based changedetection (PBCD), the object-based
change detection (OBCD), and the hybrid change detection (HCD). Nevertheless,
both PBCD and OBCD have disadvantages, and classical HCD methods belong to
intuitive decision-level fusion schemes of PBCD and OBCD. There is no optimum
HCD method as of yet. Analyzing the complementarities of PBCD and OBCD
method, we propose a new unsupervised algorithm-level fusion scheme (UAFS-
HCD) in this paper to improve the accuracy of PBCD using spatial context
information through: 1) getting the preliminary change mask with PBCD at first to
estimate some parameters for OBCD; 2) deriving the unchanged area mask to
eliminate the areas without changes, reducing error amplification phenomenon of
OBCD; and 3) obtaining the final change mask by means of OBCD method.
Taking flood detection with multitemporal SAR data as an example, we compared
the new scheme with some classical methods, including PBCD, OBCD, and HCD
method and supervised manual trial-and-error procedure (MTEP). The
experimental results of flood detection showed that the new scheme was efficient
and robust, and its accuracy sometimes can even exceed MTEP.

Software & Hardware requirement:
1. Hardware requirement:
1. PC
2. RAM minimum 2GB
3. HDD minimum 100GB
2. Software requirement:
1. MATLAB 7.0
2. Signal processing toolbox
3. Image processing toolbox
4. Mathematical toolbox
PROJECT FLOW:
First Review:
Literature Survey
Paper Explanation
Design of Project
Project Enhancement explanation
Second Review:
Implementing 40% of Base Paper
Third Review
Implementing Remaining 60% of Base Paper with Future Enhancement
(Modification)
For More Details please contact
Logic Mind Technologies
Vijayangar (Near Maruthi Medicals), Bangalore-40
Ph: 8123668124 // 8123668066
Mail: logicmindtech@gmail.com

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1. Logic Mind Technologies Vijayangar (Near Maruthi Medicals), Bangalore-40 Ph: 8123668124 // 8123668066 Title: Improving Pixel-Based Change Detection Accuracy Using an Object-Based Approach in Multitemporal SAR Flood Images Abstract—Most of existing change detection methods could be classified into three groups, the traditional pixel-based changedetection (PBCD), the object-based change detection (OBCD), and the hybrid change detection (HCD). Nevertheless, both PBCD and OBCD have disadvantages, and classical HCD methods belong to intuitive decision-level fusion schemes of PBCD and OBCD. There is no optimum HCD method as of yet. Analyzing the complementarities of PBCD and OBCD method, we propose a new unsupervised algorithm-level fusion scheme (UAFS- HCD) in this paper to improve the accuracy of PBCD using spatial context information through: 1) getting the preliminary change mask with PBCD at first to estimate some parameters for OBCD; 2) deriving the unchanged area mask to eliminate the areas without changes, reducing error amplification phenomenon of OBCD; and 3) obtaining the final change mask by means of OBCD method. Taking flood detection with multitemporal SAR data as an example, we compared the new scheme with some classical methods, including PBCD, OBCD, and HCD method and supervised manual trial-and-error procedure (MTEP). The experimental results of flood detection showed that the new scheme was efficient and robust, and its accuracy sometimes can even exceed MTEP.

2. Software & Hardware requirement: 1. Hardware requirement: 1. PC 2. RAM minimum 2GB 3. HDD minimum 100GB 2. Software requirement: 1. MATLAB 7.0 2. Signal processing toolbox 3. Image processing toolbox 4. Mathematical toolbox PROJECT FLOW: First Review: Literature Survey Paper Explanation Design of Project Project Enhancement explanation Second Review: Implementing 40% of Base Paper Third Review Implementing Remaining 60% of Base Paper with Future Enhancement (Modification) For More Details please contact Logic Mind Technologies Vijayangar (Near Maruthi Medicals), Bangalore-40 Ph: 8123668124 // 8123668066 Mail: logicmindtech@gmail.com

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