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QUALITY ASSESSMENT OF STEREOSCOPIC 3D IMAGE 
COMPRESSION BY BINOCULAR INTEGRATION BEHAVIORS 
ABSTRACT 
The objective approaches of 3D image quality assessment play a key role for the 
development of compression standards and various 3D multimedia applications. 
The quality assessment of 3D images faces more new challenges, such as asymmetric 
stereo compression, depth perception, and virtual view synthesis, than its 2D counterparts. In 
addition, the widely used 2D image quality metrics (e.g., PSNR and SSIM) cannot be directly 
applied to deal with these newly introduced challenges. 
This statement can be verified by the low correlation between the computed objective 
measures and the subjectively measured mean opinion scores (MOSs), when 3D images are the 
tested targets. In order to meet these newly introduced challenges, in this paper, besides 
traditional 2D image metrics, the binocular integration behaviors—the binocular combination 
and the binocular frequency integration, are utilized as the bases for measuring the quality of 
stereoscopic 3D images. 
The effectiveness of the proposed metrics is verified by conducting subjective evaluations 
on publicly available stereoscopic image databases. Experimental results show that significant 
consistency could be reached between the measured MOS and the proposed metrics, in which the 
correlation coefficient between them can go up to 0.88. 
Furthermore, we found that the proposed metrics can also address the quality assessment 
of the synthesized color-plus depth 3D images well. Therefore, it is our belief that the binocular 
integration behaviors are important factors in the development of objective quality assessment 
for 3D images.
ARCHITECTURE 
EXISTING SYSTEM 
Image quality assessment IQA provides the ultimate perceptual quality evaluation; the 
associated high cost and complexity handicap its value in real applications. In order to address 
this issue, computational objective IQA has long been an active research area since the last 
decade. The booming up of 3D movies and the advances in display devices, 3D image is 
becoming the new research target for IQA. The quality assessment of anaglyph 3D images was 
addressed in and the work dealt with the quality assessment of multi-camera applications (e.g. 
panorama images). One direct arisen question is the applicability of existing 2D objective 
metrics to the 3D images. 
The existing 2D quality assessment metrics can predict well for the Symmetric-Stereo 
compression, however, the prediction results are not well addressed for the Asymmetric
counterpart by the same metrics. This work aims to fill-up this gap by proposing a quality 
assessment metric which is applicable to both the Symmetric-Stereo and the Asymmetric-Stereo 
compressions. 
PROPOSED SYSTEM 
There are numerous physiological discoveries of binocular vision where we focus on the 
binocular visual behaviors that describe the visual inputs integration process. For simplicity, 
these physiological discoveries of binocular vision are denoted as binocular integration behaviors 
which consist of binocular combination and binocular frequency integration behaviors. In order 
to overcome the challenges of 3D image IQA, we integrate the binocular integration behaviors 
into the existing 2D objective metrics for evaluating the quality of 3D images. We denote the 
integrated quality assessment metrics as the Frequency-Integrated metrics 
The new challenges of 3D IQA come mainly from the interactions between the two eyes, 
a better understanding of the physiological studies of binocular vision is beneficial to the 
development of effective computational models for 3D images. We briefly revisit the findings of 
binocular vision. 
Modules 
1. Pathways of Binocular Visual System 
There are two visual pathways for neural processing of visual information in 
visual cortex, 
Dorsal stream and ventral stream 
· Dorsal stream (“Where” pathway) the dorsal stream starts from (primary visual 
cortex), goes through area. The functions of dorsal stream are about visual 
information guided actions. 
· Ventral stream (“What” pathway) the ventral stream begins from area goes 
through to area. The perception and recognition visual behaviors occur in ventral 
stream. 
(1) The visual response of two eyes,
(2) The binocular combination behaviors in the early stage of visual pathway and 
(3) The visual information representations and integration. 
2. Binocular Combination 
In this behaviors of binocular brightness combination when the input brightness is 
asymmetric in both eyes (e.g. Fechner’s paradox, cyclopean perception). 
Cyclopean perception means that we will have single perceptual image when we 
perceive 3D images/videos by two eyes. These behaviors play the role of constraints for 
selecting the plausible biological models of binocular combination. 
Fechner’s Paradox This binocular combination behavior describes the 
phenomenon that a bright light to one eye may appear less bright when a dim light is 
shown to the other eye. Cyclopean Perception The cyclopean perception was suggested 
as a constraint in the research work [65] for modeling the binocular combination 
behavior. 
3. Effect of DOG bands 
Each quality metric has its own specific visual properties and background 
assumptions, a quality metric could not perform well at DOG frequency bands which are 
far from the original usages in the regions with zero values and the original usage of VIF 
is for natural image only). 
The proposed DOG decomposition may be replaced by Gabor filter bank which is 
another popular physiological model and the corresponding performance evaluation will 
be one of our future works. 
SOFTWARE REQUIREMENTS 
Hardware Requirements
· System : Pentium IV 2.4 GHz. 
· Hard Disk : 80 GB. 
· Monitor : 15 VGA Color. 
· Mouse : Logitech. 
· Ram : 512 MB. 
Software Requirements 
· Operating system : Windows 8 (32-Bit) 
· Front End : Visual Studio 2010 
· Coding Language : C#.NET
· System : Pentium IV 2.4 GHz. 
· Hard Disk : 80 GB. 
· Monitor : 15 VGA Color. 
· Mouse : Logitech. 
· Ram : 512 MB. 
Software Requirements 
· Operating system : Windows 8 (32-Bit) 
· Front End : Visual Studio 2010 
· Coding Language : C#.NET

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Quality assessment of stereoscopic 3 d image compression by binocular integration behaviors

  • 1. QUALITY ASSESSMENT OF STEREOSCOPIC 3D IMAGE COMPRESSION BY BINOCULAR INTEGRATION BEHAVIORS ABSTRACT The objective approaches of 3D image quality assessment play a key role for the development of compression standards and various 3D multimedia applications. The quality assessment of 3D images faces more new challenges, such as asymmetric stereo compression, depth perception, and virtual view synthesis, than its 2D counterparts. In addition, the widely used 2D image quality metrics (e.g., PSNR and SSIM) cannot be directly applied to deal with these newly introduced challenges. This statement can be verified by the low correlation between the computed objective measures and the subjectively measured mean opinion scores (MOSs), when 3D images are the tested targets. In order to meet these newly introduced challenges, in this paper, besides traditional 2D image metrics, the binocular integration behaviors—the binocular combination and the binocular frequency integration, are utilized as the bases for measuring the quality of stereoscopic 3D images. The effectiveness of the proposed metrics is verified by conducting subjective evaluations on publicly available stereoscopic image databases. Experimental results show that significant consistency could be reached between the measured MOS and the proposed metrics, in which the correlation coefficient between them can go up to 0.88. Furthermore, we found that the proposed metrics can also address the quality assessment of the synthesized color-plus depth 3D images well. Therefore, it is our belief that the binocular integration behaviors are important factors in the development of objective quality assessment for 3D images.
  • 2. ARCHITECTURE EXISTING SYSTEM Image quality assessment IQA provides the ultimate perceptual quality evaluation; the associated high cost and complexity handicap its value in real applications. In order to address this issue, computational objective IQA has long been an active research area since the last decade. The booming up of 3D movies and the advances in display devices, 3D image is becoming the new research target for IQA. The quality assessment of anaglyph 3D images was addressed in and the work dealt with the quality assessment of multi-camera applications (e.g. panorama images). One direct arisen question is the applicability of existing 2D objective metrics to the 3D images. The existing 2D quality assessment metrics can predict well for the Symmetric-Stereo compression, however, the prediction results are not well addressed for the Asymmetric
  • 3. counterpart by the same metrics. This work aims to fill-up this gap by proposing a quality assessment metric which is applicable to both the Symmetric-Stereo and the Asymmetric-Stereo compressions. PROPOSED SYSTEM There are numerous physiological discoveries of binocular vision where we focus on the binocular visual behaviors that describe the visual inputs integration process. For simplicity, these physiological discoveries of binocular vision are denoted as binocular integration behaviors which consist of binocular combination and binocular frequency integration behaviors. In order to overcome the challenges of 3D image IQA, we integrate the binocular integration behaviors into the existing 2D objective metrics for evaluating the quality of 3D images. We denote the integrated quality assessment metrics as the Frequency-Integrated metrics The new challenges of 3D IQA come mainly from the interactions between the two eyes, a better understanding of the physiological studies of binocular vision is beneficial to the development of effective computational models for 3D images. We briefly revisit the findings of binocular vision. Modules 1. Pathways of Binocular Visual System There are two visual pathways for neural processing of visual information in visual cortex, Dorsal stream and ventral stream · Dorsal stream (“Where” pathway) the dorsal stream starts from (primary visual cortex), goes through area. The functions of dorsal stream are about visual information guided actions. · Ventral stream (“What” pathway) the ventral stream begins from area goes through to area. The perception and recognition visual behaviors occur in ventral stream. (1) The visual response of two eyes,
  • 4. (2) The binocular combination behaviors in the early stage of visual pathway and (3) The visual information representations and integration. 2. Binocular Combination In this behaviors of binocular brightness combination when the input brightness is asymmetric in both eyes (e.g. Fechner’s paradox, cyclopean perception). Cyclopean perception means that we will have single perceptual image when we perceive 3D images/videos by two eyes. These behaviors play the role of constraints for selecting the plausible biological models of binocular combination. Fechner’s Paradox This binocular combination behavior describes the phenomenon that a bright light to one eye may appear less bright when a dim light is shown to the other eye. Cyclopean Perception The cyclopean perception was suggested as a constraint in the research work [65] for modeling the binocular combination behavior. 3. Effect of DOG bands Each quality metric has its own specific visual properties and background assumptions, a quality metric could not perform well at DOG frequency bands which are far from the original usages in the regions with zero values and the original usage of VIF is for natural image only). The proposed DOG decomposition may be replaced by Gabor filter bank which is another popular physiological model and the corresponding performance evaluation will be one of our future works. SOFTWARE REQUIREMENTS Hardware Requirements
  • 5. · System : Pentium IV 2.4 GHz. · Hard Disk : 80 GB. · Monitor : 15 VGA Color. · Mouse : Logitech. · Ram : 512 MB. Software Requirements · Operating system : Windows 8 (32-Bit) · Front End : Visual Studio 2010 · Coding Language : C#.NET
  • 6. · System : Pentium IV 2.4 GHz. · Hard Disk : 80 GB. · Monitor : 15 VGA Color. · Mouse : Logitech. · Ram : 512 MB. Software Requirements · Operating system : Windows 8 (32-Bit) · Front End : Visual Studio 2010 · Coding Language : C#.NET