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SUBMITTED BY SUMIT G RAUT VINOD S RAUT MANGESH N NIMSE PROJECT GUIDE Dr. Mrs. K.R.JOSHI
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Page 1: Quality assessment of 3 d

SUBMITTED BY

SUMIT G RAUT

VINOD S RAUT

MANGESH N NIMSE

PROJECT GUIDE

Dr. Mrs. K.R.JOSHI

Page 2: Quality assessment of 3 d

• What is quality assessment of images?

• What are the parameters related 2D/3D images?

• How 3D images are created(possible geometry)?

• What are available algorithms to assess image quality?

• Many more(etc…)

Page 3: Quality assessment of 3 d

• It refers to creation of algorithms that gauge the perceived

quality of the visual stimuli.

• Since the ultimate receiver of any visual stimulus is a

human observer, his/her opinion of quality is what is of

import and is referred to as percieved quality of stimulus.

Page 4: Quality assessment of 3 d

• Visual stimulus is a generic term that encompasses 2D

images,2D videos, 3D images, 3D videos, immersive

viewing environments and so on.

• Essentially, any captured stimulus that is incident upon

the eyes is referred to as a visual stimulus.

• There are two types of QA :

1)objective QA

2)subjective QA

Page 5: Quality assessment of 3 d

Objective algorithms themselves are generally

categorized as

(1) full-reference (FR),

(2) no-reference (NR) and

(3) Reduced-reference (RR) algorithms

Page 6: Quality assessment of 3 d
Page 7: Quality assessment of 3 d

There are 26 parameters available for 2d imaging

They are based upon various properties like stuctural

geometry,human vision perception,distortion etc..

Eg.SSIM,HVS,SNR resp..

Page 8: Quality assessment of 3 d

3D content is expected to make the transition from

movie theaters into living rooms .

Increasing peoples demand over 3D viewing expriences

Research and development and Study the new depths

for enhanced quality of images and videos.

Page 9: Quality assessment of 3 d

To study 3D image we need to know Visual Depth

Cues:

Monoscopic Depth Cues (single 2D image)

Stereoscopic Depth Cues (two 2D images)

Motion Depth Cues (series of 2D images)

Physiological Depth Cues (body cues)

Page 10: Quality assessment of 3 d

Interposition◦ An object that occludes another is closer

Shading◦ Shape info. Shadows are included here

Size◦ Usually, the larger object is closer

Linear Perspective◦ parallel lines converge at a single point

Surface Texture Gradient◦ more detail for closer objects

Height in the visual field◦ Higher the object is (vertically), the further it is

Atmospheric effects ◦ further away objects are blurrier

Brightness◦ further away objects are dimmer

Page 11: Quality assessment of 3 d

Y

Z

X

Page 12: Quality assessment of 3 d

Left and right-eye views of an image are computed and

alternately displayed on the screen.

A shuttering system occludes the right eye when the

left-eye image is being displayed and occludes the left-

eye when the right-eye image is being displayed.

Page 13: Quality assessment of 3 d

SSIM

UQI

C4

Page 14: Quality assessment of 3 d

stereo TV

3D display

entertainment(videos, games)

Practical Applications like Image filtering &

compression and medical imaging etc.

Page 15: Quality assessment of 3 d

Experiments and evaluations for QA using SSIM and

UQI QM’s.

There implementation using ‘MATLAB’ or ‘C’.

A database of various images is required to collect on

which the code will be implemented.

Survey on its application on a real-time basis like in

medical imaging science, ‘THE SIXTH SENSE’, 3D

displays of hand-held devices and a lot more.

Page 16: Quality assessment of 3 d

[1] Anush K. Moorthy , Student Member, IEEE and Alan C. Bovik, Member, IEEE

,Research Article “Visual Quality Assessment Algorithms : What Does the Future

Hold?”

[2] Alexandre Benoit, Patrick Le Callet (EURASIPMember),Patrizio Campisi

(EURASIPMember),and Romain Cousseau,Research Article “Quality Assessment of

Stereoscopic Images”, EURASIP Journal on Image and Video Processing Volume

2008, Article ID 659024, 13 pages doi:10.1155/2008/659024

[3]Alan C. Bovik ,LIVE, “LIVE Color+3D Database,”http://live.ece.utexas.edu.

[4] N. Ponomarenko, V. Lukin, A. Zelensky, K. Egiazarian, M. Carli, F. Battisti,

"TID2008 - A Database for Evaluation of Full-Reference Visual Quality Assessment

Metrics", Advances of Modern Radioelectronics, Vol. 10, pp. 30-45, 2009.

Page 17: Quality assessment of 3 d

[5] ZHOU WANG AND ALAN C. BOVIK , “UNIVERSAL IMAGE QUALITY

INDEX” IEEE SIGNAL PROCESSING MARCH-2002.

[6] Zhou Wang, Member, IEEE, Alan C. Bovik, Fellow, IEEE Hamid R. Sheikh,

Student Member, IEEE, and Eero P. Simoncelli, Senior Member, IEEE, “Image Quality

Assessment: From Error Visibility to Structural Similarity”, IEEE TRANSACTIONS

ON IMAGE PROCESSING, VOL. 13, NO. 4, APRIL 2004

Page 18: Quality assessment of 3 d