| Autor: |
Bosakova-Ardenska, Atanaska, Andreeva, Hristina |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2024, Vol. 3063 Issue 1, p1-13, 13p |
| Abstrakt: |
As an essential operation filtering is a well-known technique for images smoothing and denoising on the level of primary images processing. Due to its computational complexity there are many approaches for decreasing its time complexity and the most often used one is the parallel processing. This paper presents a potential to improve effectiveness of images filtering by usage of computer system with multi-core architecture and message passing interface (MPI) library for communication among parallel processes. Two parallel algorithms for linear filtering are implemented and tested with two sets of experimental images. First algorithm is based on classic mean filter, but second algorithm uses partial sums in order to accelerate performance. It is observed that increasing number of parallel processes, decrease measured processing time when the number of parallel processes is not bigger than number of computational cores. Time performance of filtering process depends on size of used mask (kernel) also and increasing of mask size leads to significant increase of processing time. This effect is weaker presented when the algorithm for filtering uses partial sums. The experimental results based on processing on three different computer systems indicates that the best speed-up is achieved when the number of parallel processes is equal to number of computational cores and its value is about 4. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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