prikaz prve stranice dokumenta UKLANJANJE ŠUMA IZ BIOMEDICINSKIH SLIKA KORIŠTENJEM ADAPTIVNIH ALGORITAMA TEMELJENIH NA PRESJECIŠTU INTERVALA POUZDANOSTI
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master's thesis
UKLANJANJE ŠUMA IZ BIOMEDICINSKIH SLIKA KORIŠTENJEM ADAPTIVNIH ALGORITAMA TEMELJENIH NA PRESJECIŠTU INTERVALA POUZDANOSTI
2018. urn:nbn:hr:190:180815
Mandić, Ivica
University of Rijeka
Faculty of Engineering

Cite this document

Mandić, I. (2018). UKLANJANJE ŠUMA IZ BIOMEDICINSKIH SLIKA KORIŠTENJEM ADAPTIVNIH ALGORITAMA TEMELJENIH NA PRESJECIŠTU INTERVALA POUZDANOSTI (Master's thesis). Rijeka: University of Rijeka, Faculty of Engineering. Retrieved from https://urn.nsk.hr/urn:nbn:hr:190:180815

Mandić, Ivica. "UKLANJANJE ŠUMA IZ BIOMEDICINSKIH SLIKA KORIŠTENJEM ADAPTIVNIH ALGORITAMA TEMELJENIH NA PRESJECIŠTU INTERVALA POUZDANOSTI." Master's thesis, University of Rijeka, Faculty of Engineering, 2018. https://urn.nsk.hr/urn:nbn:hr:190:180815

Mandić, Ivica. "UKLANJANJE ŠUMA IZ BIOMEDICINSKIH SLIKA KORIŠTENJEM ADAPTIVNIH ALGORITAMA TEMELJENIH NA PRESJECIŠTU INTERVALA POUZDANOSTI." Master's thesis, University of Rijeka, Faculty of Engineering, 2018. https://urn.nsk.hr/urn:nbn:hr:190:180815

Mandić, I. (2018). 'UKLANJANJE ŠUMA IZ BIOMEDICINSKIH SLIKA KORIŠTENJEM ADAPTIVNIH ALGORITAMA TEMELJENIH NA PRESJECIŠTU INTERVALA POUZDANOSTI', Master's thesis, University of Rijeka, Faculty of Engineering, accessed 18 October 2024, https://urn.nsk.hr/urn:nbn:hr:190:180815

Mandić I. UKLANJANJE ŠUMA IZ BIOMEDICINSKIH SLIKA KORIŠTENJEM ADAPTIVNIH ALGORITAMA TEMELJENIH NA PRESJECIŠTU INTERVALA POUZDANOSTI [Master's thesis]. Rijeka: University of Rijeka, Faculty of Engineering; 2018 [cited 2024 October 18] Available at: https://urn.nsk.hr/urn:nbn:hr:190:180815

I. Mandić, "UKLANJANJE ŠUMA IZ BIOMEDICINSKIH SLIKA KORIŠTENJEM ADAPTIVNIH ALGORITAMA TEMELJENIH NA PRESJECIŠTU INTERVALA POUZDANOSTI", Master's thesis, University of Rijeka, Faculty of Engineering, Rijeka, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:190:180815

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TitleUKLANJANJE ŠUMA IZ BIOMEDICINSKIH SLIKA KORIŠTENJEM ADAPTIVNIH ALGORITAMA TEMELJENIH NA PRESJECIŠTU INTERVALA POUZDANOSTI
Title (english)Denoising of X-ray Images Using the Adaptive Algorithm Based on the LPA-RICI Algorithm
AuthorIvica Mandić
MentorJonatan Lerga (mentor)
Committee memberKristijan Lenac (predsjednik povjerenstva)
GranterUniversity of Rijeka
Faculty of Engineering
Rijeka
Defense date and country2018-03, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Diagnostics and treatments of numerous diseases are highly dependent on the quality of captured medical images. However, noise (during both acquisition and transmission) is one oft he main factors that reduce their quality.This paper proposes an adaptive image denoising algorithm applied to enhance X-ray images.The algorithm is based on the modification oft he intersection of confidence intervals (ICI) rule,called relative intersection of confidence intervals (RICI) rule. For each image pixel apart,a 2D mask of adaptive size and shape is calculated and used in designing the 2D local polynomial approximation (LPA) filters for noise removal. One of the advantages of the proposed method is the fact that the estimation of the noise free pixel is performed in dependently for each image pixel and thus, the method is applicable for easy parallelization in order to improve its computational efficiency. The proposed method was compared to the Gaussian smoothing filters, total variation denoising and fixed size median filtering and was shown to outperform them both visually and in terms of the peak signal to-noise ratio (PSNR) by up to 7.99 dB.
Keywords
Languagecroatian
URN:NBNurn:nbn:hr:190:180815
Study programmeTitle: Computer Engineering
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsAccess restricted to students and staff of home institution
Terms of useLicence In copyright icon
Created on2018-04-10 12:19:29