SMART SENSOR: AN ON-BOARD IMAGE PROCESSING SYSTEM FOR REAL-TIME REMOTE SENSING

2002 ◽  
Vol 02 (03) ◽  
pp. 481-499
Author(s):  
JANE YOU ◽  
DAVID ZHANG
Keyword(s):  
Remote Sensing ◽  
Image Analysis ◽  
Image Compression ◽  
Real Time ◽  
Processing System ◽  
Smart Sensor ◽  
Pipeline Architecture ◽  
New Approach ◽  
Hardware Processing ◽  
Sensor System Design

This paper presents a new approach to smart sensor system design for real-time remote sensing. A combination of techniques for image analysis and image compression is investigated. The proposed algorithms include: (1) a fractional discrimination function for image analysis, (2) a comparison of effective algorithms for image compression, (3) a pipeline architecture for parallel image classification and compression on-board satellites, and (4) a task control strategy for mapping image computing models to hardware processing elements. The efficiency and accuracy of the proposed techniques are demonstrated throughout system simulation.

scholarly journals AN INSTANTANEOUS POINT SOURCE DETECTION AND EXTRACTION SYSTEM FOR GEO REMOTE SENSING SATELLITE

2018 ◽  
Vol XLII-3 ◽  
pp. 451-454
Author(s):  
Y. Guo ◽  
Q. Li ◽  
W. Wu
Keyword(s):  
Remote Sensing ◽  
Point Source ◽  
Real Time ◽  
Processing System ◽  
Image Data ◽  
Source Detection ◽  
Source Information ◽  
Real Time Processing ◽  
Time Processing ◽  
Instantaneous Point

To accomplish the task of detecting the instantaneous point source, an on-board information real-time processing system is designed which can process the point-source detection with reconfigurable function. The system has the algorithm reconfigurable function, which can detect and extract the instantaneous point source from the remote sensing image. By using FPGA programming, the satellite target detection and processing algorithm can be update easily. At the same time, the software can be reconfigured to improve the system's information processing capabilities. The system has been verified by simulating real instantaneous source point target image data to meet the real-time processing requirements of instantaneous point source information detection.

scholarly journals A Web Application Exhibiting Parking Guidance using Smart Sensor Networks

2020 ◽  
Vol 9 (4) ◽  
pp. 2430-2434
Keyword(s):  
User Interface ◽  
Sensor Networks ◽  
Real Time ◽  
Web Application ◽  
Smart Sensor ◽  
Ultrasonic Sensors ◽  
New Approach ◽  
Cloud Database ◽  
Smart Parking ◽  
Base Application

Smart parking is the digital approach to the modern-day parking problems. This project presents a new approach to the parking problems in our country in which we use ultrasonic sensors to detect the unoccupied places inside the parking area. This data is frequently captured and updated onto a real time cloud database. From that database we fetch the details of the parking area and present it to the end customer in the form of a web base application. This application will show the end customer where are the unoccupied slots are located and the path to that unoccupied space is presented onto the User Interface so that the user can park his car in a very limited amount of time.

Image Processing Technology for Aerial Camera Manipulator

2014 ◽  
Vol 644-650 ◽  
pp. 4072-4075
Author(s):  
Zheng Liang ◽  
Jian An Yuan
Keyword(s):  
Image Processing ◽  
Image Compression ◽  
Real Time ◽  
Processing System ◽  
Processing Technology ◽  
Storage Space ◽  
Image Information ◽  
Aircraft Systems ◽  
Wavelet Coding ◽  
Important Means

CCD aerial camera is one of the important means of obtaining the image information on the ground, it is through the collection, archiving, and reading to achieved the images acquisition. As the very large amounts of data of the images, it takes a lot of time far more than analysis and processing when archiving and reading, so that not only difficult achieve real-time detection and processing, but also causing a waste of storage space. Therefore, the research of image compression and other processing technology has become important particularly.This paper use the wavelet coding to get images compression for the problem, and design the image processing system of aerial camera manipulator. This system designed by embedded modular, and ARINC 429 bus to achieve communications between the camera and the aircraft systems, make compression to the images which captured by the camera, and deal with the compressed image as stored, local zoom in and out, etc.

Design of real-time remote sensing image compression system

2013 ◽  
Author(s):  
Wenbo Wu ◽  
Ning Lei ◽  
Kun Wang ◽  
Qingyuan Wang ◽  
Tao Li
Keyword(s):  
Remote Sensing ◽  
Image Compression ◽  
Real Time ◽  
Remote Sensing Image ◽  
Compression System

scholarly journals Single-chip multi-processing architecture for spaceborne SAR imaging and intelligent processing

2021 ◽  
Vol 39 (3) ◽  
pp. 510-520
Author(s):  
Shiyu Wang ◽  
Shengbing Zhang ◽  
Xiaoping Huang ◽  
Libo Chang
Keyword(s):  
Remote Sensing ◽  
Power Consumption ◽  
Real Time ◽  
Processing System ◽  
Data Organization ◽  
Single Chip ◽  
Processing Scheme ◽  
Intelligent Processing ◽  
High Efficient ◽  
Processing Architecture

The satellite-borne SAR image intelligent processing system needs to process on-orbit real-time imaging and various tasks of applications, for which reason designing a dedicated high-efficient single-chip multi-processor is of prioritized necessity that can simultaneously satisfy requirements of real-time and low power consumption. Aiming at on-chip data organization and memory access structure, two typical models of SAR(synthetic aperture radar) imaging CSA (chirp scaling) and neural network VGG-11 are analyzed, and then a collaborative computing model for the intelligent processing on remote sensing is extracted. A strip Tile data processing scheme and a dedicated multi-processing architecture is not only proposed, but a data organization and a caching strategy of Tile space synchronization splicing is also presented. In addition, the designed data caching structure among the processing units greatly reduces off-chip access memory bandwidth while supporting parallel pipeline execution of multi-task model. The chip adopts 28 nm CMOS technology featuring with merely 1.83 W of the overall power consumption, whose throughput and energy efficiency reaches 9.89TOPS and 5.4 TOPS/W, respectively. The present architecture can improve real-time performance of the on-orbit remote sensing intelligent processing platform while reducing the complexity of system designing, which is highly adaptive to differentiated expansions according to different models of algorithm.

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