Perceptual image rendering

Given a limited computation budget, perceptual image rendering aims to produce synthesized images with higher perceived quality than uniformly rendered ones by exploiting the properties of the human visual system (HVS). There are several perceptual models that have been used in the rendering process...

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Main Author: Low, Yih Fei.
Other Authors: Lin Weisi
Format: Final Year Project
Language:English
Published: 2012
Subjects:
Online Access:http://hdl.handle.net/10356/49135
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-491352023-03-03T20:47:14Z Perceptual image rendering Low, Yih Fei. Lin Weisi School of Computer Engineering Centre for Multimedia and Network Technology DRNTU::Engineering::Computer science and engineering::Computing methodologies::Computer graphics Given a limited computation budget, perceptual image rendering aims to produce synthesized images with higher perceived quality than uniformly rendered ones by exploiting the properties of the human visual system (HVS). There are several perceptual models that have been used in the rendering process, such as the human visual attention (VA) model and the human visual system (HVS) model. In this project, the just noticeable difference (JND) model is explored. The JND model represents the change of the sensitivity of the HVS with the spatial frequency of image contents. The sensitivity decreases on high frequency patterns and this allows a higher level of error to be tolerated. Different from the VA model which describes a global characteristic of the image contents, the JND model describes a local characteristic of the image contents. Therefore, a perceptual model is proposed by combining the JND model with the VA model and the combined VA-JND model is applied in the adaptive sampling process of image rendering. Experiments have been performed to analyse the difference between images rendered perceptually with the VA model only and images rendered with the combined VA-JND model. The experimental results that the combined VA-JND model can further improve the quality of images rendered with the VA model only, within a given sample budget. Bachelor of Engineering (Computer Science) 2012-05-15T03:43:24Z 2012-05-15T03:43:24Z 2012 2012 Final Year Project (FYP) http://hdl.handle.net/10356/49135 en Nanyang Technological University 43 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::Computer graphics
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Computer graphics
Low, Yih Fei.
Perceptual image rendering
description Given a limited computation budget, perceptual image rendering aims to produce synthesized images with higher perceived quality than uniformly rendered ones by exploiting the properties of the human visual system (HVS). There are several perceptual models that have been used in the rendering process, such as the human visual attention (VA) model and the human visual system (HVS) model. In this project, the just noticeable difference (JND) model is explored. The JND model represents the change of the sensitivity of the HVS with the spatial frequency of image contents. The sensitivity decreases on high frequency patterns and this allows a higher level of error to be tolerated. Different from the VA model which describes a global characteristic of the image contents, the JND model describes a local characteristic of the image contents. Therefore, a perceptual model is proposed by combining the JND model with the VA model and the combined VA-JND model is applied in the adaptive sampling process of image rendering. Experiments have been performed to analyse the difference between images rendered perceptually with the VA model only and images rendered with the combined VA-JND model. The experimental results that the combined VA-JND model can further improve the quality of images rendered with the VA model only, within a given sample budget.
author2 Lin Weisi
author_facet Lin Weisi
Low, Yih Fei.
format Final Year Project
author Low, Yih Fei.
author_sort Low, Yih Fei.
title Perceptual image rendering
title_short Perceptual image rendering
title_full Perceptual image rendering
title_fullStr Perceptual image rendering
title_full_unstemmed Perceptual image rendering
title_sort perceptual image rendering
publishDate 2012
url http://hdl.handle.net/10356/49135
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