NDLI: Histogram-based cost aggregation strategy with joint bilateral filtering for stereo matching

Please wait, while we are loading the content...

Graphics processing unit-accelerated multi-resolution exhaustive search algorithm for real-time keypoint descriptor matching in high-dimensional spaces

Histogram-based cost aggregation strategy with joint bilateral filtering for stereo matching

Local directional mask maximum edge patterns for image retrieval and face recognition

Parallel algorithm implementation for multi-object tracking and surveillance

Supervised framework for automatic recognition and retrieval of interaction: a framework for classification and retrieving videos with similar human interactions

Volume 10 (2016) : Issue 2, Mar

Volume 10 (2016) : Issue 1, Feb

IET Computers & Digital Techniques

IET Control Theory & Applications

IET Cyber-Physical Systems: Theory & Applications

IET Cyber-Systems and Robotics

IET Electric Power Applications

IET Electrical Systems in Transportation

IET Energy Systems Integration

IET Generation, Transmission & Distribution

IET Image Processing

IET Information Security

IET Intelligent Transport Systems

IET Microwaves, Antennas & Propagation

IET Nanobiotechnology

IET Nanodielectrics

IET Networks

IET Optoelectronics

IET Power Electronics

IET Quantum Communication

IET Radar, Sonar & Navigation

IET Renewable Power Generation

IET Science, Measurement & Technology

IET Signal Processing

IET Wireless Sensor Systems

Micro & Nano Letters

The Journal of Engineering

Histogram-based cost aggregation strategy with joint bilateral filtering for stereo matching

Content Provider	IET Digital Library
Author	Fu, Limei Peng, Guohua Song, Weijie
Abstract	The edge-aware bilateral filter has been demonstrated to be effective for preserving depth edges, and disparity maps obtained from Fast Bilateral Stereo (FBS) have enhanced the efficiency of algorithm and the robustness to noise. However, they also lead to a non-perfect localisation of discontinuities. To overcome this issue, a new bilateral filtering based cost aggregation utilising colour statistical classification and similarity measurement within annular blocks is proposed in this study. We have adopted the similarity of histograms evaluated by Earth Mover Distance (EMD) to obtain the raw matching cost in the raised annular block, since histograms are very effective and efficient in capturing the distribution characteristics of visual features. For the weights aggregation, the spatial weight is assumed to be a constant. The colour weight is calculated by using a cluster-mean-value strategy, which is implemented by the local colour histogram. It improves the accuracy in the discontinuous areas. Computation redundancy is reduced by disparity candidate selection using the local minimal relevancy in the corresponding annular blocks. We use the efficiency and accuracy to demonstrate the performance of our proposed method. Experimental results have shown that the proposed method reduces the mismatch at depth discontinuous and the computation complexity significantly.
Starting Page	173
Ending Page	181
Page Count	9
ISSN	17519632
Volume Number	10
e-ISSN	17519640
Issue Number	Issue 3, Apr (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/10/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2014.0411
Journal	IET Computer Vision
Publisher Date	2016-04-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Bilateral Filtering Based Cost Aggregation Strategy Cluster-mean-value Strategy Colour Histogram Statistical Classification Computation Complexity Computer Vision And Image Processing Technique Disparity Candidate Selection Earth Mover Distance Edge-aware Bilateral Filter Filtering Method in Signal Processing Filtering Theory Histogram-based Cost Aggregation Strategy Image Colour Analysis Image Enhancement Image Matching Image Recognition Similarity Measurement Statistical Analysis Statistics Stereo Image Processing Stereo Matching
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

Estimation of disparity map of stereo image pairs using spatial domain local Gabor wavelet

Joint Histogram-Based Cost Aggregation for Stereo Matching

Cost-volume filtering-based stereo matching with improved matching cost and secondary refinement

Hardware-Efficient Bilateral Filtering for Stereo Matching

Stereo Disparity through Cost Aggregation with Guided Filter

Cross-Trees for Stereo Matching with Priors

Ieee transaction on pattern analysis and machine intelligence 1 joint histogram based cost aggregation for stereo matching.

Stereo Matching Based on Efficient Image-Guided Cost Aggregation

Real-time stereo using approximated joint bilateral filtering and dynamic programming

Histogram-based cost aggregation strategy with joint bilateral filtering for stereo matching

Similar Documents

Estimation of disparity map of stereo image pairs using spatial domain local Gabor wavelet

Joint Histogram-Based Cost Aggregation for Stereo Matching

Cost-volume filtering-based stereo matching with improved matching cost and secondary refinement

Hardware-Efficient Bilateral Filtering for Stereo Matching

Stereo Disparity through Cost Aggregation with Guided Filter

Cross-Trees for Stereo Matching with Priors

Ieee transaction on pattern analysis and machine intelligence 1 joint histogram based cost aggregation for stereo matching.

Stereo Matching Based on Efficient Image-Guided Cost Aggregation

Real-time stereo using approximated joint bilateral filtering and dynamic programming

Histogram-based cost aggregation strategy with joint bilateral filtering for stereo matching