TY - GEN
T1 - Many-core parallel algorithm to correct the gaussian noise of an image
AU - Alvarez-Sanchez, Teodoro
AU - Alvarez-Cedillo, Jesus A.
AU - Sandoval-Gutierrez, Jacobo
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2019.
PY - 2019
Y1 - 2019
N2 - The digitization of information is abundant in different areas related to digital image processing; its primary objective is to improve the quality of the image for a correct human interpretation or to facilitate the search of information patterns in a shorter time, with fewer computing resources, size and low energy consumption. This research is focused on validating a possible implementation using a limited embedded system, so the specified processing speed and algorithms that redistribute the computational cost are required. The strategy has been based on parallel processing for the distribution of tasks and data to the Epiphany III. It was combined to reduce the factors that introduce noise to the image and improve quality. The most common types of noise are Gaussian noise, impulsive noise, uniform noise and speckle noise. In this paper, the effects of Gaussian noise that occurs at the moment of the acquisition of the image that produces as a consequence blur in some pixels of the image is analyzed, and that generates the effect of haze (blur). The implementation was developed using the Many-core technology in 2 × 2 and 4 × 4 arrays with (4, 8, 16) cores, also the performance of the Epiphany system was characterized to FFT2D, FFT setup, BITREV, FFT1D, Corner turn and LPF and the response times in machine cycles of each algorithm are shown. The power of parallel processing with this technology is displayed, and the low power consumption is related to the number of cores used. The contribution of this research in a qualitative way is demonstrated with a slight variation for the human eye in each other images tested, and finally, the method is a useful tool for applications with resources limited.
AB - The digitization of information is abundant in different areas related to digital image processing; its primary objective is to improve the quality of the image for a correct human interpretation or to facilitate the search of information patterns in a shorter time, with fewer computing resources, size and low energy consumption. This research is focused on validating a possible implementation using a limited embedded system, so the specified processing speed and algorithms that redistribute the computational cost are required. The strategy has been based on parallel processing for the distribution of tasks and data to the Epiphany III. It was combined to reduce the factors that introduce noise to the image and improve quality. The most common types of noise are Gaussian noise, impulsive noise, uniform noise and speckle noise. In this paper, the effects of Gaussian noise that occurs at the moment of the acquisition of the image that produces as a consequence blur in some pixels of the image is analyzed, and that generates the effect of haze (blur). The implementation was developed using the Many-core technology in 2 × 2 and 4 × 4 arrays with (4, 8, 16) cores, also the performance of the Epiphany system was characterized to FFT2D, FFT setup, BITREV, FFT1D, Corner turn and LPF and the response times in machine cycles of each algorithm are shown. The power of parallel processing with this technology is displayed, and the low power consumption is related to the number of cores used. The contribution of this research in a qualitative way is demonstrated with a slight variation for the human eye in each other images tested, and finally, the method is a useful tool for applications with resources limited.
KW - Frequency domain
KW - Gaussian noise
KW - Many-core
KW - Parallel algorithms
KW - Parallel processing
UR - http://www.scopus.com/inward/record.url?scp=85059884454&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-10448-1_7
DO - 10.1007/978-3-030-10448-1_7
M3 - Contribución a la conferencia
AN - SCOPUS:85059884454
SN - 9783030104474
T3 - Communications in Computer and Information Science
SP - 70
EP - 86
BT - Supercomputing - 9th International Conference, ISUM 2018, Revised Selected Papers
A2 - Gitler, Isidoro
A2 - Klapp, Jaime
A2 - Tchernykh, Andrei
A2 - Torres, Moises
PB - Springer Verlag
T2 - 9th International Conference on Supercomputing, ISUM 2018
Y2 - 5 March 2018 through 9 March 2018
ER -