Naslov
Directional image denoising method based on the relative intersection of confidence intervals rule

Autori
Seršić, Damir ; Sović, Ana

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
EUROCON 2013 / - Zagreb, 2013, 1593-1597

Skup
EUROCON

Mjesto i datum
Zagreb, Hrvatska, 01.07.2013. - 04.07.2013

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Intersection of confidence intervals; image denoising; mean; median; adaptive filters

Sažetak
In this paper, the relative intersection of confidence intervals (ICI) rule is used to adaptively determine window sizes around each observed point in purpose of denoising. The relative ICI rule defines neighbourhoods of similar statistical properties for every signal sample. If we calculate a mean value on each window, it corresponds to the zero-order estimation and results in a denoised signal. Furthermore, the mean value can be replaced by median for additional robustness of estimation. The same approach could be taken on images. In this paper, we find the maximum window length in four, eight or sixteen directions around each pixel. Mean or median value of chosen surrounding pixels results in a denoised estimation of each observed pixel. The proposed denoising method was tested on an example of a piece-wise constant image and compared to known methods. Under the given conditions, it has shown improvement in terms of the PSNR, MAE and subjective visual impression.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo

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