Denoising of X-ray Images Using the Adaptive Algorithm Based on the LPA-RICI Algorithm
AbstractDiagnostics 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. View Full-Text
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Mandić, I.; Peić, H.; Lerga, J.; Štajduhar, I. Denoising of X-ray Images Using the Adaptive Algorithm Based on the LPA-RICI Algorithm. J. Imaging 2018, 4, 34.
Mandić I, Peić H, Lerga J, Štajduhar I. Denoising of X-ray Images Using the Adaptive Algorithm Based on the LPA-RICI Algorithm. Journal of Imaging. 2018; 4(2):34.Chicago/Turabian Style
Mandić, Ivica; Peić, Hajdi; Lerga, Jonatan; Štajduhar, Ivan. 2018. "Denoising of X-ray Images Using the Adaptive Algorithm Based on the LPA-RICI Algorithm." J. Imaging 4, no. 2: 34.
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