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Hardware Acceleration of Most Apparent Distortion Image Quality Assessment Algorithm on FPGA Using OpenCL.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Hardware Acceleration of Most Apparent Distortion Image Quality Assessment Algorithm on FPGA Using OpenCL./
Author:	Gunavelu Mohan, Aswin.
Description:	1 online resource (66 pages)
Notes:	Source: Masters Abstracts International, Volume: 56-04.
Contained By:	Masters Abstracts International56-04(E).
Subject:	Electrical engineering. -
Online resource:	click for full text (PQDT)
ISBN:	9781369776065

Hardware Acceleration of Most Apparent Distortion Image Quality Assessment Algorithm on FPGA Using OpenCL.
Gunavelu Mohan, Aswin.

Hardware Acceleration of Most Apparent Distortion Image Quality Assessment Algorithm on FPGA Using OpenCL. - 1 online resource (66 pages)

Source: Masters Abstracts International, Volume: 56-04.

Thesis (M.S.)--Arizona State University, 2017.

Includes bibliographical references

The information era has brought about many technological advancements in the past few decades, and that has led to an exponential increase in the creation of digital images and videos. Constantly, all digital images go through some image processing algorithm for various reasons like compression, transmission, storage, etc. There is data loss during this process which leaves us with a degraded image. Hence, to ensure minimal degradation of images, the requirement for quality assessment has become mandatory. Image Quality Assessment (IQA) has been researched and developed over the last several decades to predict the quality score in a manner that agrees with human judgments of quality. Modern image quality assessment (IQA) algorithms are quite effective at prediction accuracy, and their development has not focused on improving computational performance. The existing serial implementation requires a relatively large run-time on the order of seconds for a single frame. Hardware acceleration using Field programmable gate arrays (FPGAs) provides reconfigurable computing fabric that can be tailored for a broad range of applications. Usually, programming FPGAs has required expertise in hardware descriptive languages (HDLs) or high-level synthesis (HLS) tool. OpenCL is an open standard for cross-platform, parallel programming of heterogeneous systems along with Altera OpenCL SDK, enabling developers to use FPGA's potential without extensive hardware knowledge. Hence, this thesis focuses on accelerating the computationally intensive part of the most apparent distortion (MAD) algorithm on FPGA using OpenCL. The results are compared with CPU implementation to evaluate performance and efficiency gains.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369776065Subjects--Topical Terms:

596380
Electrical engineering.
Index Terms--Genre/Form:

554714
Electronic books.

Hardware Acceleration of Most Apparent Distortion Image Quality Assessment Algorithm on FPGA Using OpenCL.
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500 $a Source: Masters Abstracts International, Volume: 56-04.
500 $a Advisers: Sohum Sohoni; Fengbo Ren.
502 $a Thesis (M.S.)--Arizona State University, 2017.
504 $a Includes bibliographical references
520 $a The information era has brought about many technological advancements in the past few decades, and that has led to an exponential increase in the creation of digital images and videos. Constantly, all digital images go through some image processing algorithm for various reasons like compression, transmission, storage, etc. There is data loss during this process which leaves us with a degraded image. Hence, to ensure minimal degradation of images, the requirement for quality assessment has become mandatory. Image Quality Assessment (IQA) has been researched and developed over the last several decades to predict the quality score in a manner that agrees with human judgments of quality. Modern image quality assessment (IQA) algorithms are quite effective at prediction accuracy, and their development has not focused on improving computational performance. The existing serial implementation requires a relatively large run-time on the order of seconds for a single frame. Hardware acceleration using Field programmable gate arrays (FPGAs) provides reconfigurable computing fabric that can be tailored for a broad range of applications. Usually, programming FPGAs has required expertise in hardware descriptive languages (HDLs) or high-level synthesis (HLS) tool. OpenCL is an open standard for cross-platform, parallel programming of heterogeneous systems along with Altera OpenCL SDK, enabling developers to use FPGA's potential without extensive hardware knowledge. Hence, this thesis focuses on accelerating the computationally intensive part of the most apparent distortion (MAD) algorithm on FPGA using OpenCL. The results are compared with CPU implementation to evaluate performance and efficiency gains.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
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