Fast distortion measurement using Chord-Length parameterization within the Vertex-Based rate-distortion optimal shape coding framework

F.A. Sohel; G.C. Karmakar; L.S. Dooley

doi:10.1109/LSP.2006.882099

Back

Fast distortion measurement using Chord-Length parameterization within the Vertex-Based rate-distortion optimal shape coding framework

Journal article

Open access

Peer reviewed

Fast distortion measurement using Chord-Length parameterization within the Vertex-Based rate-distortion optimal shape coding framework

F.A. Sohel, G.C. Karmakar and L.S. Dooley

IEEE Signal Processing Letters, Vol.14(2), pp.121-124

2007

DOI: https://doi.org/10.1109/LSP.2006.882099

Files and links (2)

pdf

fast_distortion.pdfDownload View

Published (Version of Record) Open Access

url

Link to Published Version *Subscription may be requiredView

Abstract

Existing vertex-based operational rate-distortion (ORD) optimal shape coding algorithms can use a number of different distortion measurement techniques, including the shortest absolute distance (SAD), the distortion band (DB), the tolerance band (TB), and the accurate distortion measurement technique for shape coding (ADMSC). From a computational time perspective, an -point contour requires O(N2) time for DB and TB for both polygon and B-spline-based encoding, while SAD and ADMSC incur O(N) time for polygonal encoding but O(N2) for B-spline based encoding, thereby rendering the ORD optimal algorithms computationally inefficient. This letter presents a novel distortion measurement strategy based on chord-length parameterization (DMCLP) of a boundary that incurs order O(N) complexity for both polygon and B-spline-based encoding while preserving a comparable rate-distortion performance to the original ORD optimal shape coding algorithms.

Details

Title: Fast distortion measurement using Chord-Length parameterization within the Vertex-Based rate-distortion optimal shape coding framework
Authors/Creators: F.A. Sohel (Author/Creator) - Monash University
G.C. Karmakar (Author/Creator) - Monash University
L.S. Dooley (Author/Creator) - Monash University
Publication Details: IEEE Signal Processing Letters, Vol.14(2), pp.121-124
Publisher: IEEE
Identifiers: 991005544858207891
Murdoch Affiliation: Murdoch University
Language: English
Resource Type: Journal article

Metrics

152 File views/ downloads

72 Record Views

10 Times Cited - Web of Science

InCites Highlights

These are selected metrics from InCites Benchmarking & Analytics tool, related to this output

Collaboration types: Domestic collaboration
Citation topics: 4 Electrical Engineering, Electronics & Computer Science; 4.101 Security, Encryption & Encoding; 4.101.178 Video Coding
Web Of Science research areas: Engineering, Electrical & Electronic
ESI research areas: Engineering