東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back to Search results for [ null ]

Switch To: Labeled | MARC Mode | ISBD

Real time mitigation of atmospheric ...

Jackson, Christopher Robert.

Linked to FindBook

Google Book

Amazon

博客來

Real time mitigation of atmospheric turbulence in long distance imaging using the lucky region fusion algorithm with FPGA and GPU hardware acceleration.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Real time mitigation of atmospheric turbulence in long distance imaging using the lucky region fusion algorithm with FPGA and GPU hardware acceleration./
Author:	Jackson, Christopher Robert.
Description:	72 p.
Notes:	Source: Masters Abstracts International, Volume: 55-01.
Contained By:	Masters Abstracts International55-01(E).
Subject:	Computer engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1596862
ISBN:	9781321989465

Real time mitigation of atmospheric turbulence in long distance imaging using the lucky region fusion algorithm with FPGA and GPU hardware acceleration.
Jackson, Christopher Robert.

Real time mitigation of atmospheric turbulence in long distance imaging using the lucky region fusion algorithm with FPGA and GPU hardware acceleration. - 72 p.

Source: Masters Abstracts International, Volume: 55-01.

Thesis (M.S.)--University of Delaware, 2015.

"Lucky-region" fusion (LRF) is a synthetic imaging technique that has proven successful in enhancing the quality of images distorted by atmospheric turbulence. The LRF algorithm selects sharp regions of an image obtained from a series of short exposure frames, and fuses the sharp regions into a final, improved image. In previous research, the LRF algorithm had been implemented on a PC using the C programming language. However, the PC did not have sufficient sequential processing power to handle real-time extraction, processing and reduction required when the LRF algorithm was applied to real-time video from fast, high-resolution image sensors. This thesis describes two hardware implementations of the LRF algorithm to achieve real-time image processing. The first was created with a VIRTEX-7 field programmable gate array (FPGA). The other developed using the graphics processing unit (GPU) of a NVIDIA GeForce GTX 690 video card. The novelty in the FPGA approach is the creation of a "black box" LRF video processing system with a general camera link input, a user controller interface, and a camera link video output. We also describe a custom hardware simulation environment we have built to test the FPGA LRF implementation. The advantage of the GPU approach is significantly improved development time, integration of image stabilization into the system, and comparable atmospheric turbulence mitigation.

ISBN: 9781321989465Subjects--Topical Terms:

621879
Computer engineering.

Real time mitigation of atmospheric turbulence in long distance imaging using the lucky region fusion algorithm with FPGA and GPU hardware acceleration.
LDR:02359nmm a2200289 4500 001 2068663
005 20160428074919.5
008 170521s2015 ||||||||||||||||| ||eng d
020 $a 9781321989465
035 $a (MiAaPQ)AAI1596862
035 $a AAI1596862
040 $a MiAaPQ $c MiAaPQ
100 1 $a Jackson, Christopher Robert. $3 3183619
245 1 0 $a Real time mitigation of atmospheric turbulence in long distance imaging using the lucky region fusion algorithm with FPGA and GPU hardware acceleration.
300 $a 72 p.
500 $a Source: Masters Abstracts International, Volume: 55-01.
500 $a Adviser: Fouad E. Kiamilev.
502 $a Thesis (M.S.)--University of Delaware, 2015.
520 $a "Lucky-region" fusion (LRF) is a synthetic imaging technique that has proven successful in enhancing the quality of images distorted by atmospheric turbulence. The LRF algorithm selects sharp regions of an image obtained from a series of short exposure frames, and fuses the sharp regions into a final, improved image. In previous research, the LRF algorithm had been implemented on a PC using the C programming language. However, the PC did not have sufficient sequential processing power to handle real-time extraction, processing and reduction required when the LRF algorithm was applied to real-time video from fast, high-resolution image sensors. This thesis describes two hardware implementations of the LRF algorithm to achieve real-time image processing. The first was created with a VIRTEX-7 field programmable gate array (FPGA). The other developed using the graphics processing unit (GPU) of a NVIDIA GeForce GTX 690 video card. The novelty in the FPGA approach is the creation of a "black box" LRF video processing system with a general camera link input, a user controller interface, and a camera link video output. We also describe a custom hardware simulation environment we have built to test the FPGA LRF implementation. The advantage of the GPU approach is significantly improved development time, integration of image stabilization into the system, and comparable atmospheric turbulence mitigation.
590 $a School code: 0060.
650 4 $a Computer engineering. $3 621879
650 4 $a Electrical engineering. $3 649834
650 4 $a Optics. $3 517925
690 $a 0464
690 $a 0544
690 $a 0752
710 2 $a University of Delaware. $b Electrical and Computer Engineering. $3 3183620
773 0 $t Masters Abstracts International $g 55-01(E).
790 $a 0060
791 $a M.S.
792 $a 2015
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1596862