Pregled bibliografske jedinice broj: 933243
Adaptivni algoritmi za uklanjanje šuma temeljeni na presjecištu intervala pouzdanosti primijenjeni na biomedicinske slike
Adaptivni algoritmi za uklanjanje šuma temeljeni na presjecištu intervala pouzdanosti primijenjeni na biomedicinske slike, 2018., diplomski rad, diplomski, Tehnički fakultet, Rijeka doi:10.3390/jimaging4020034
CROSBI ID: 933243 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Adaptivni algoritmi za uklanjanje šuma temeljeni na presjecištu intervala pouzdanosti primijenjeni na biomedicinske slike
(Adaptive algorithms for denoising based on the intersection of confidence intervals applied to biomedical images)
Autori
Peić, Hajdi
Vrsta, podvrsta i kategorija rada
Ocjenski radovi, diplomski rad, diplomski
Fakultet
Tehnički fakultet
Mjesto
Rijeka
Datum
04.04
Godina
2018
Stranica
24
Mentor
Lerga, Jonatan
Ključne riječi
adaptive filtering ; relative intersection of confidence interval (RICI) algorithm ; image denoising ; medical imaging
Sažetak
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 of the 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 of the 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 independently 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.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo