A fast and robust map-based superresolution reconstruction method using cdhs and block-wise motion vector selection

Hsi Kuan Chen, Chin-Hsing Chen, Shih Jen Wang

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

High computational complexity and occlusion including the extreme case of a scene change, are, the two most, critical problems in super-resolution (SR) reconstruction. In this paper, we adopted the Cross-Diamond-Hexagonal Search (CDHS) block-matching algorithm (BMA) to reduce the complexity significantly. The CDHS BMA reduced about 2/3 computation time without sacrificing the reconstruction quality comparable to the full search BMA but it has high, noises, unqualified motion vectors, resulted, from occlusion existing in each frame of a sequence. We further proposed a simple and robust block-wise motion vector selection (BWMVS) strategy that can remove occlusion effectively. The stability due to BWMVS was verified by the reconstruction results using the interpolation methods (nearest, bilinear, and bicubic). The experimental results showed that by combining the CDHS BMA and BWMVS, high quality images in SR reconstruction can be obtained without complex computation. ICIC International

Original languageEnglish
Pages (from-to)3105-3120
Number of pages16
JournalInternational Journal of Innovative Computing, Information and Control
Volume6
Issue number7
Publication statusPublished - 2010 Jul 1

Fingerprint

Block Algorithm
Block Matching
Motion Vector
Super-resolution
Matching Algorithm
Strombus or kite or diamond
Occlusion
Hexagon
Diamonds
Interpolation Method
Image Quality
Image quality
Computational complexity
Interpolation
Computational Complexity
Extremes
Experimental Results

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Information Systems
  • Computational Theory and Mathematics

Cite this

@article{57a23466b7384e10bac4bc38fb8b1da6,
title = "A fast and robust map-based superresolution reconstruction method using cdhs and block-wise motion vector selection",
abstract = "High computational complexity and occlusion including the extreme case of a scene change, are, the two most, critical problems in super-resolution (SR) reconstruction. In this paper, we adopted the Cross-Diamond-Hexagonal Search (CDHS) block-matching algorithm (BMA) to reduce the complexity significantly. The CDHS BMA reduced about 2/3 computation time without sacrificing the reconstruction quality comparable to the full search BMA but it has high, noises, unqualified motion vectors, resulted, from occlusion existing in each frame of a sequence. We further proposed a simple and robust block-wise motion vector selection (BWMVS) strategy that can remove occlusion effectively. The stability due to BWMVS was verified by the reconstruction results using the interpolation methods (nearest, bilinear, and bicubic). The experimental results showed that by combining the CDHS BMA and BWMVS, high quality images in SR reconstruction can be obtained without complex computation. ICIC International",
author = "Chen, {Hsi Kuan} and Chin-Hsing Chen and Wang, {Shih Jen}",
year = "2010",
month = "7",
day = "1",
language = "English",
volume = "6",
pages = "3105--3120",
journal = "International Journal of Innovative Computing, Information and Control",
issn = "1349-4198",
publisher = "IJICIC Editorial Office",
number = "7",

}

TY - JOUR

T1 - A fast and robust map-based superresolution reconstruction method using cdhs and block-wise motion vector selection

AU - Chen, Hsi Kuan

AU - Chen, Chin-Hsing

AU - Wang, Shih Jen

PY - 2010/7/1

Y1 - 2010/7/1

N2 - High computational complexity and occlusion including the extreme case of a scene change, are, the two most, critical problems in super-resolution (SR) reconstruction. In this paper, we adopted the Cross-Diamond-Hexagonal Search (CDHS) block-matching algorithm (BMA) to reduce the complexity significantly. The CDHS BMA reduced about 2/3 computation time without sacrificing the reconstruction quality comparable to the full search BMA but it has high, noises, unqualified motion vectors, resulted, from occlusion existing in each frame of a sequence. We further proposed a simple and robust block-wise motion vector selection (BWMVS) strategy that can remove occlusion effectively. The stability due to BWMVS was verified by the reconstruction results using the interpolation methods (nearest, bilinear, and bicubic). The experimental results showed that by combining the CDHS BMA and BWMVS, high quality images in SR reconstruction can be obtained without complex computation. ICIC International

AB - High computational complexity and occlusion including the extreme case of a scene change, are, the two most, critical problems in super-resolution (SR) reconstruction. In this paper, we adopted the Cross-Diamond-Hexagonal Search (CDHS) block-matching algorithm (BMA) to reduce the complexity significantly. The CDHS BMA reduced about 2/3 computation time without sacrificing the reconstruction quality comparable to the full search BMA but it has high, noises, unqualified motion vectors, resulted, from occlusion existing in each frame of a sequence. We further proposed a simple and robust block-wise motion vector selection (BWMVS) strategy that can remove occlusion effectively. The stability due to BWMVS was verified by the reconstruction results using the interpolation methods (nearest, bilinear, and bicubic). The experimental results showed that by combining the CDHS BMA and BWMVS, high quality images in SR reconstruction can be obtained without complex computation. ICIC International

UR - http://www.scopus.com/inward/record.url?scp=77955195315&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77955195315&partnerID=8YFLogxK

M3 - Article

VL - 6

SP - 3105

EP - 3120

JO - International Journal of Innovative Computing, Information and Control

JF - International Journal of Innovative Computing, Information and Control

SN - 1349-4198

IS - 7

ER -