Modification of Non-local Mean Algorithm Using Parallel Calculation for Image Noise Reduction

Al Farissi; Wondo Wondo

doi:10.23887/janapati.v12i2.58996

Authors

Al Farissi Universitas Sriwijaya
Wondo Wondo Information Technology Division, Bank Rakyat Indonesia

DOI:

https://doi.org/10.23887/janapati.v12i2.58996

Keywords:

digital image, noise reduction, euclidean distance , gaussian noise, Non-local Mean algorithm

Abstract

Noise in digital image processing is a noise that occurs at pixel values due to random colour intensity. Several types of noise models include Gaussian noise, speckle noise, impulse noise, and Poisson noise. Before processing image data, a noise reduction process is required. One of the noise reduction algorithms used for gaussian noise models is Non-local Mean. This algorithm performs calculations sequentially on each pixel in the search block. Due to a large number of pixels and search block area in the image, the noise reduction process using the Non-local Mean algorithm is very slow. This study proposes the concept of parallel calculations for the Non-local Mean algorithm. This concept divides the search block into three parts and performs calculations on each part simultaneously. The experimental results show that the Non-local Mean algorithm with parallel calculations can reduce noise up to 30% faster if the noise standard deviation is above 30.

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