{"title":"Parsytec GCel 3/512计算机视觉算法","authors":"P. Nastou, K. Kyrimis, D. Maritsas","doi":"10.1109/ICAPP.1995.472209","DOIUrl":null,"url":null,"abstract":"This paper describes the implementation of a library of low-level image processing algorithms. This library is divided into two families of algorithms, one for those that apply to the spatial domain (local histogram equalization, local average filter, median filter, Sobel edge detector, and histogram evaluation), and one for those that apply to the frequency domain (forward and inverse discrete Fourier Transform, amplitude of the forward discrete Fourier transform, forward and inverse discrete cosine transform, and Butterworth filters). The efficiency of these algorithms depends on the number of processors used, the method of combining results produced by different processors (e.g., sequentially or using a binary tree), and the time required for the combination of two independently produced results compared to the time required to produce them.<<ETX>>","PeriodicalId":448130,"journal":{"name":"Proceedings 1st International Conference on Algorithms and Architectures for Parallel Processing","volume":"155 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Computer vision algorithms on the Parsytec GCel 3/512\",\"authors\":\"P. Nastou, K. Kyrimis, D. Maritsas\",\"doi\":\"10.1109/ICAPP.1995.472209\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes the implementation of a library of low-level image processing algorithms. This library is divided into two families of algorithms, one for those that apply to the spatial domain (local histogram equalization, local average filter, median filter, Sobel edge detector, and histogram evaluation), and one for those that apply to the frequency domain (forward and inverse discrete Fourier Transform, amplitude of the forward discrete Fourier transform, forward and inverse discrete cosine transform, and Butterworth filters). The efficiency of these algorithms depends on the number of processors used, the method of combining results produced by different processors (e.g., sequentially or using a binary tree), and the time required for the combination of two independently produced results compared to the time required to produce them.<<ETX>>\",\"PeriodicalId\":448130,\"journal\":{\"name\":\"Proceedings 1st International Conference on Algorithms and Architectures for Parallel Processing\",\"volume\":\"155 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-04-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 1st International Conference on Algorithms and Architectures for Parallel Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAPP.1995.472209\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 1st International Conference on Algorithms and Architectures for Parallel Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAPP.1995.472209","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Computer vision algorithms on the Parsytec GCel 3/512
This paper describes the implementation of a library of low-level image processing algorithms. This library is divided into two families of algorithms, one for those that apply to the spatial domain (local histogram equalization, local average filter, median filter, Sobel edge detector, and histogram evaluation), and one for those that apply to the frequency domain (forward and inverse discrete Fourier Transform, amplitude of the forward discrete Fourier transform, forward and inverse discrete cosine transform, and Butterworth filters). The efficiency of these algorithms depends on the number of processors used, the method of combining results produced by different processors (e.g., sequentially or using a binary tree), and the time required for the combination of two independently produced results compared to the time required to produce them.<>