The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
다중 해상도 이미지를 사용하는 계층적 접근 방식은 품질 저하 없이 계산량을 줄이는 잘 알려진 기술입니다. 이미지 프로세서를 설계할 때 가장 큰 문제 중 하나는 간단한 상호 연결 네트워크로 병렬 액세스를 지원하는 메모리 시스템을 설계하는 것입니다. 상호 연결 네트워크의 복잡성은 주로 메모리 할당에 따라 달라집니다. 이는 픽셀을 메모리 모듈에 매핑하고 필요한 메모리 모듈 수를 결정합니다. 본 논문에서는 다중해상도 영상을 이용한 영상처리를 위해 메모리 모듈 수를 최소화하기 위한 메모리 할당 방법을 제시한다. 효율적인 검색을 위해 제안하는 방법은 윈도우 형태의 영상 처리의 규칙성을 활용한다. 실제 사례에서는 메모리 모듈 수가 기존 방식에 비해 14% 미만으로 줄어드는 것을 보여줍니다.
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부
Yasuhiro KOBAYASHI, Masanori HARIYAMA, Michitaka KAMEYAMA, "Memory Allocation for Multi-Resolution Image Processing" in IEICE TRANSACTIONS on Information,
vol. E91-D, no. 10, pp. 2386-2397, October 2008, doi: 10.1093/ietisy/e91-d.10.2386.
Abstract: Hierarchical approaches using multi-resolution images are well-known techniques to reduce the computational amount without degrading quality. One major issue in designing image processors is to design a memory system that supports parallel access with a simple interconnection network. The complexity of the interconnection network mainly depends on memory allocation; it maps pixels onto memory modules and determines the required number of memory modules. This paper presents a memory allocation method to minimize the number of memory modules for image processing using multi-resolution images. For efficient search, the proposed method exploits the regularity of window-type image processing. A practical example demonstrates that the number of memory modules is reduced to less than 14% that of conventional methods.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e91-d.10.2386/_p
부
@ARTICLE{e91-d_10_2386,
author={Yasuhiro KOBAYASHI, Masanori HARIYAMA, Michitaka KAMEYAMA, },
journal={IEICE TRANSACTIONS on Information},
title={Memory Allocation for Multi-Resolution Image Processing},
year={2008},
volume={E91-D},
number={10},
pages={2386-2397},
abstract={Hierarchical approaches using multi-resolution images are well-known techniques to reduce the computational amount without degrading quality. One major issue in designing image processors is to design a memory system that supports parallel access with a simple interconnection network. The complexity of the interconnection network mainly depends on memory allocation; it maps pixels onto memory modules and determines the required number of memory modules. This paper presents a memory allocation method to minimize the number of memory modules for image processing using multi-resolution images. For efficient search, the proposed method exploits the regularity of window-type image processing. A practical example demonstrates that the number of memory modules is reduced to less than 14% that of conventional methods.},
keywords={},
doi={10.1093/ietisy/e91-d.10.2386},
ISSN={1745-1361},
month={October},}
부
TY - JOUR
TI - Memory Allocation for Multi-Resolution Image Processing
T2 - IEICE TRANSACTIONS on Information
SP - 2386
EP - 2397
AU - Yasuhiro KOBAYASHI
AU - Masanori HARIYAMA
AU - Michitaka KAMEYAMA
PY - 2008
DO - 10.1093/ietisy/e91-d.10.2386
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E91-D
IS - 10
JA - IEICE TRANSACTIONS on Information
Y1 - October 2008
AB - Hierarchical approaches using multi-resolution images are well-known techniques to reduce the computational amount without degrading quality. One major issue in designing image processors is to design a memory system that supports parallel access with a simple interconnection network. The complexity of the interconnection network mainly depends on memory allocation; it maps pixels onto memory modules and determines the required number of memory modules. This paper presents a memory allocation method to minimize the number of memory modules for image processing using multi-resolution images. For efficient search, the proposed method exploits the regularity of window-type image processing. A practical example demonstrates that the number of memory modules is reduced to less than 14% that of conventional methods.
ER -