Implementation of image compression on hardware platform

The image compression in which I use is JPEG. JPEG has been around for many decades and it has also been a standardized means of image transmission. For JPEG, there are lossless and lossy compression. Lossy compression will be implemented for this project. Lossy compression will result in a lower qu...

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Main Author: Koh, Aloysius Jia Lun
Other Authors: Ho Duan Juat
Format: Final Year Project
Language:English
Published: 2018
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Online Access:http://hdl.handle.net/10356/74553
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-745532023-07-07T15:54:34Z Implementation of image compression on hardware platform Koh, Aloysius Jia Lun Ho Duan Juat School of Electrical and Electronic Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision The image compression in which I use is JPEG. JPEG has been around for many decades and it has also been a standardized means of image transmission. For JPEG, there are lossless and lossy compression. Lossy compression will be implemented for this project. Lossy compression will result in a lower quality image as compared to the original, but it requires fewer resources and lower latency. The values and test image are according to industry’s standard and will be implemented as a means of testing the algorithm effectiveness on Zedboard and on a hardware platform. Given that the coding and methods used were simple and not effective, it would only be a rough comparison. “Lena”, a standardized test image was converted to RGB format and adjusted to 256 x 256 resolution, prior to the compression, to accommodate for the low storage space. The image will be converted to YCrCb color space for the JPEG compression and back to RGB, to be displayed through a 12-bit VGA cable to a monitor. The quantization stage of the JPEG compression algorithm determines the quality of the decompressed output image. The higher the quality factor, the lower the compression but higher the output quality. Multiple quality factors in a factor of 10 from 0 to 100 are being tested. However, there are some setbacks. The internal memory of the BRAM is not large enough to support a Q-factor of above 80. As a result, only Q-factor from 0-80 are manipulated. Bachelor of Engineering 2018-05-21T07:19:06Z 2018-05-21T07:19:06Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/74553 en Nanyang Technological University 82 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Koh, Aloysius Jia Lun
Implementation of image compression on hardware platform
description The image compression in which I use is JPEG. JPEG has been around for many decades and it has also been a standardized means of image transmission. For JPEG, there are lossless and lossy compression. Lossy compression will be implemented for this project. Lossy compression will result in a lower quality image as compared to the original, but it requires fewer resources and lower latency. The values and test image are according to industry’s standard and will be implemented as a means of testing the algorithm effectiveness on Zedboard and on a hardware platform. Given that the coding and methods used were simple and not effective, it would only be a rough comparison. “Lena”, a standardized test image was converted to RGB format and adjusted to 256 x 256 resolution, prior to the compression, to accommodate for the low storage space. The image will be converted to YCrCb color space for the JPEG compression and back to RGB, to be displayed through a 12-bit VGA cable to a monitor. The quantization stage of the JPEG compression algorithm determines the quality of the decompressed output image. The higher the quality factor, the lower the compression but higher the output quality. Multiple quality factors in a factor of 10 from 0 to 100 are being tested. However, there are some setbacks. The internal memory of the BRAM is not large enough to support a Q-factor of above 80. As a result, only Q-factor from 0-80 are manipulated.
author2 Ho Duan Juat
author_facet Ho Duan Juat
Koh, Aloysius Jia Lun
format Final Year Project
author Koh, Aloysius Jia Lun
author_sort Koh, Aloysius Jia Lun
title Implementation of image compression on hardware platform
title_short Implementation of image compression on hardware platform
title_full Implementation of image compression on hardware platform
title_fullStr Implementation of image compression on hardware platform
title_full_unstemmed Implementation of image compression on hardware platform
title_sort implementation of image compression on hardware platform
publishDate 2018
url http://hdl.handle.net/10356/74553
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