{"title":"采用先进先出和自适应数据压缩的0.5V功率和面积效率的拉普拉斯金字塔处理引擎","authors":"S. Zeinolabedin, Jun Zhou, Xin Liu, T. T. Kim","doi":"10.1109/ESSCIRC.2015.7313839","DOIUrl":null,"url":null,"abstract":"This paper proposes a power and area efficient Laplacian Pyramid processing engine (LPPE) for multi-resolution image representation in image/video processing. In the proposed LPPE, a novel FIFO architecture with adaptive data compression is proposed to reduce the power and area consumption of LPPE. A new filtering extension method is also proposed to reduce the output errors. In circuit level, near-threshold design is adopted to further reduce the power consumption by supply voltage scaling. The proposed LPPE fabricated in a 0.18 μm CMOS process technology can process 112 frames per second at 3.68 MHz and 0.5 V while consuming only 452 μW.","PeriodicalId":11845,"journal":{"name":"ESSCIRC Conference 2015 - 41st European Solid-State Circuits Conference (ESSCIRC)","volume":"2 1","pages":"104-107"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A 0.5V power and area efficient Laplacian Pyramid processing engine using FIFO with adaptive data compression\",\"authors\":\"S. Zeinolabedin, Jun Zhou, Xin Liu, T. T. Kim\",\"doi\":\"10.1109/ESSCIRC.2015.7313839\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a power and area efficient Laplacian Pyramid processing engine (LPPE) for multi-resolution image representation in image/video processing. In the proposed LPPE, a novel FIFO architecture with adaptive data compression is proposed to reduce the power and area consumption of LPPE. A new filtering extension method is also proposed to reduce the output errors. In circuit level, near-threshold design is adopted to further reduce the power consumption by supply voltage scaling. The proposed LPPE fabricated in a 0.18 μm CMOS process technology can process 112 frames per second at 3.68 MHz and 0.5 V while consuming only 452 μW.\",\"PeriodicalId\":11845,\"journal\":{\"name\":\"ESSCIRC Conference 2015 - 41st European Solid-State Circuits Conference (ESSCIRC)\",\"volume\":\"2 1\",\"pages\":\"104-107\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ESSCIRC Conference 2015 - 41st European Solid-State Circuits Conference (ESSCIRC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ESSCIRC.2015.7313839\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ESSCIRC Conference 2015 - 41st European Solid-State Circuits Conference (ESSCIRC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ESSCIRC.2015.7313839","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A 0.5V power and area efficient Laplacian Pyramid processing engine using FIFO with adaptive data compression
This paper proposes a power and area efficient Laplacian Pyramid processing engine (LPPE) for multi-resolution image representation in image/video processing. In the proposed LPPE, a novel FIFO architecture with adaptive data compression is proposed to reduce the power and area consumption of LPPE. A new filtering extension method is also proposed to reduce the output errors. In circuit level, near-threshold design is adopted to further reduce the power consumption by supply voltage scaling. The proposed LPPE fabricated in a 0.18 μm CMOS process technology can process 112 frames per second at 3.68 MHz and 0.5 V while consuming only 452 μW.