High Efficiency Sensing in Real Time

被引：0
|
作者：
Liu, Xiteng [1 ]
机构：
[1] LucidSee Technol, Toronto, ON, Canada
来源：
REAL-TIME IMAGE PROCESSING AND DEEP LEARNING 2022 | 2022年 / 12102卷
关键词：
Compressed sensing; high efficiency sensing; least square boost; orthogonal system theorem; RECOVERY;
D O I：
10.1117/12.2614236
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
We exemplify a new mathematical theory and method for high efficiency sensing in real time, in contrast to compressed sensing theory, which is the most sensational topic of scientific research in the past century. Compared with compressed sensing, high efficiency sensing radically rectifies mathematical rationale while immensely improves technical performance. Based on discovery of new logical phenomenon, we make a broad spectrum of innovations on rationale, methodology, transform, techniques and so on, which working together result in dominant improvement in terms of both data quality and computation speed. High efficiency denotes high quality plus high speed. The pivotal innovation is simple yet powerful. Demo software and test data are both downloadable at our website www.lucidsee.ca
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页数：9
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