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Performance Comparison of Image Enhancement Algorithms Evaluated on Poor Quality Images
Blekinge Institute of Technology, Faculty of Engineering, Department of Applied Signal Processing.
Blekinge Institute of Technology, Faculty of Engineering, Department of Applied Signal Processing.
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Many applications require automatic image analysis for different quality of the input images. In many cases, the quality of acquired images is suitable for the purpose of the application. However, in some cases the quality of the acquired image has to be modified according to needs of a specific application. A higher quality of the image can be achieved by Image Enhancement (IE) algorithms. The choice of IE technique is challenging as this choice varies with the application purpose. The goal of this research is to investigate the possibility of the selective application for the IE algorithms. The values of entropy and Peak Signal to Noise Ratio (PSNR) of the acquired image are considered as parameters for selectivity. Three algorithms such as Retinex, Bilateral filter and Bilateral tone adjustment have been chosen as IE techniques for evaluation in this work. Entropy and PSNR are used for the performance evaluation of selected IE algorithms. In this study, we considered the images from three fingerprint image databases as input images to investigate the algorithms. The decision to enhance an image in these databases by the considered algorithms is based on the empirically evaluated entropy and PSNR thresholds. Automatic Fingerprint Identification System (AFIS) has been selected as the application of interest. The evaluation results show that the performance of the investigated IE algorithms affects significantly the performance of AFIS. The second conclusion is that entropy and PSNR might be considered as indicators for required IE of the input image for AFIS.

Place, publisher, year, edition, pages
2017. , 81 p.
Keyword [en]
Image Enhancement, Retinex, Bilateral Filter, Bilateral Tone Adjustment, PSNR, Entropy, AFIS
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:bth-13880OAI: oai:DiVA.org:bth-13880DiVA: diva2:1071513
Subject / course
ET2566 Master's Thesis (120 credits) in Electrical Engineering with emphasis on Signal processing
Educational program
ETASX Master of Science Programme in Electrical Engineering with emphasis on Signal Processing
Presentation
2016-09-28, J1620, Blekinge Institute Of Technology, Karlskrona, Sweden, 14:30 (English)
Supervisors
Examiners
Available from: 2017-02-06 Created: 2017-02-05 Last updated: 2017-02-06Bibliographically approved

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BTH2017Kotha(10976 kB)246 downloads
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Department of Applied Signal Processing
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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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