T. Hamamoto, Y. Egi, M. Hatori, K. Aizawa, T. Okubo, H. Maruyama, E. Fossum
{"title":"Computational image sensors for on-sensor-compression","authors":"T. Hamamoto, Y. Egi, M. Hatori, K. Aizawa, T. Okubo, H. Maruyama, E. Fossum","doi":"10.1109/MNNFS.1996.493806","DOIUrl":null,"url":null,"abstract":"In this paper, we propose novel image sensors which compress image signal. By making use of very fast analog processing on the imager plane, the compression sensor can significantly reduce the amount of pixel data output from the sensor. The proposed sensor is intended to overcome the communication bottle neck for high pixel rate imaging such as high frame rate imaging and high resolution imaging. The compression sensor consists of three parts; transducer, memory and processor. Two architectures for on-sensor-compression are discussed in this paper that are pixel parallel architecture and column parallel architecture. In the former architecture, the three parts are put together in each pixel, and processing is pixel parallel. In the latter architecture, transducer, processor and memory areas are separated, and processing is column parallel. We also describe a prototype chip of pixel-parallel-type sensor with 32/spl times/32 pixels which has been fabricated using 2 /spl mu/m CMOS technology. Some results of examinations are shown in this paper.","PeriodicalId":151891,"journal":{"name":"Proceedings of Fifth International Conference on Microelectronics for Neural Networks","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of Fifth International Conference on Microelectronics for Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MNNFS.1996.493806","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In this paper, we propose novel image sensors which compress image signal. By making use of very fast analog processing on the imager plane, the compression sensor can significantly reduce the amount of pixel data output from the sensor. The proposed sensor is intended to overcome the communication bottle neck for high pixel rate imaging such as high frame rate imaging and high resolution imaging. The compression sensor consists of three parts; transducer, memory and processor. Two architectures for on-sensor-compression are discussed in this paper that are pixel parallel architecture and column parallel architecture. In the former architecture, the three parts are put together in each pixel, and processing is pixel parallel. In the latter architecture, transducer, processor and memory areas are separated, and processing is column parallel. We also describe a prototype chip of pixel-parallel-type sensor with 32/spl times/32 pixels which has been fabricated using 2 /spl mu/m CMOS technology. Some results of examinations are shown in this paper.
本文提出了一种新型的图像传感器,可以对图像信号进行压缩。通过利用成像平面上非常快速的模拟处理,压缩传感器可以显著减少传感器输出的像素数据量。该传感器旨在克服高帧率成像和高分辨率成像等高像素率成像的通信瓶颈。压缩传感器由三部分组成;传感器、存储器和处理器。本文讨论了两种传感器上的并行结构:像素并行结构和列并行结构。在前一种架构中,这三个部分放在每个像素上,并且处理是像素并行的。在后一种体系结构中,传感器、处理器和存储区是分开的,处理是列并行的。我们还描述了一种采用2/spl μ m CMOS技术制作的32/spl倍/32像素像素并行式传感器原型芯片。本文给出了一些检验结果。