An image enhancement technique based on wavelets

Hae Sung Lee, Yongbum Cho, Hyeran Byun, Jisang Yoo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

We propose a technique for image enhancement, especially for denoising and deblocking based on wavelets. In this proposed algorithm, a frame wavelet system designed as an optimal edge detector is used. And our theory depends on Lipschitz regularity, spatial correlation, and some important assumptions. The performance of the proposed algorithm is tested on three popular test images in image processing area. Experimental results show that the performance of the proposed algorithm is better than those of other previous denoising techniques like spatial averaging filter, Gaussian filter, median filter, Wiener filter, and some other wavelet based filters in the aspect of both PSNR and human visual system. The experimental results also show that our algorithm has approximately same capability of deblocking as those of previous developed techniques.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsTomaso Poggio, Seong-Whan Lee, Heinrich H. Bulthoff
PublisherSpringer Verlag
Pages286-296
Number of pages11
ISBN (Print)3540675604, 9783540675600
DOIs
Publication statusPublished - 2000 Jan 1
Event1st IEEE International Workshop on Biologically Motivated Computer Vision, BMCV 2000 - Seoul, Korea, Republic of
Duration: 2000 May 152000 May 17

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1811
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st IEEE International Workshop on Biologically Motivated Computer Vision, BMCV 2000
CountryKorea, Republic of
CitySeoul
Period00/5/1500/5/17

Fingerprint

Image Enhancement
Image enhancement
Wavelets
Denoising
Filter
Gaussian Filter
Wiener Filter
Wavelet Frames
Median Filter
Median filters
Human Visual System
Experimental Results
Spatial Correlation
Averaging
Lipschitz
Image Processing
Image processing
Regularity
Detector
Detectors

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Lee, H. S., Cho, Y., Byun, H., & Yoo, J. (2000). An image enhancement technique based on wavelets. In T. Poggio, S-W. Lee, & H. H. Bulthoff (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 286-296). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1811). Springer Verlag. https://doi.org/10.1007/3-540-45482-9_28
Lee, Hae Sung ; Cho, Yongbum ; Byun, Hyeran ; Yoo, Jisang. / An image enhancement technique based on wavelets. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). editor / Tomaso Poggio ; Seong-Whan Lee ; Heinrich H. Bulthoff. Springer Verlag, 2000. pp. 286-296 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Lee, HS, Cho, Y, Byun, H & Yoo, J 2000, An image enhancement technique based on wavelets. in T Poggio, S-W Lee & HH Bulthoff (eds), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1811, Springer Verlag, pp. 286-296, 1st IEEE International Workshop on Biologically Motivated Computer Vision, BMCV 2000, Seoul, Korea, Republic of, 00/5/15. https://doi.org/10.1007/3-540-45482-9_28

An image enhancement technique based on wavelets. / Lee, Hae Sung; Cho, Yongbum; Byun, Hyeran; Yoo, Jisang.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). ed. / Tomaso Poggio; Seong-Whan Lee; Heinrich H. Bulthoff. Springer Verlag, 2000. p. 286-296 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1811).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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T1 - An image enhancement technique based on wavelets

AU - Lee, Hae Sung

AU - Cho, Yongbum

AU - Byun, Hyeran

AU - Yoo, Jisang

PY - 2000/1/1

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N2 - We propose a technique for image enhancement, especially for denoising and deblocking based on wavelets. In this proposed algorithm, a frame wavelet system designed as an optimal edge detector is used. And our theory depends on Lipschitz regularity, spatial correlation, and some important assumptions. The performance of the proposed algorithm is tested on three popular test images in image processing area. Experimental results show that the performance of the proposed algorithm is better than those of other previous denoising techniques like spatial averaging filter, Gaussian filter, median filter, Wiener filter, and some other wavelet based filters in the aspect of both PSNR and human visual system. The experimental results also show that our algorithm has approximately same capability of deblocking as those of previous developed techniques.

AB - We propose a technique for image enhancement, especially for denoising and deblocking based on wavelets. In this proposed algorithm, a frame wavelet system designed as an optimal edge detector is used. And our theory depends on Lipschitz regularity, spatial correlation, and some important assumptions. The performance of the proposed algorithm is tested on three popular test images in image processing area. Experimental results show that the performance of the proposed algorithm is better than those of other previous denoising techniques like spatial averaging filter, Gaussian filter, median filter, Wiener filter, and some other wavelet based filters in the aspect of both PSNR and human visual system. The experimental results also show that our algorithm has approximately same capability of deblocking as those of previous developed techniques.

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Lee HS, Cho Y, Byun H, Yoo J. An image enhancement technique based on wavelets. In Poggio T, Lee S-W, Bulthoff HH, editors, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2000. p. 286-296. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/3-540-45482-9_28