Image quality analysis
Image quality analysis is becoming more an d more important in this digital age. The main objective of image quality analysis is to study the quality of image s and develop methods to efficiently and swiftly determine the quality of images. This project aims to study...
| Main Author: | |
|---|---|
| Format: | Final Year Project Report / IMRAD |
| Language: | English English |
| Published: |
Universiti Malaysia Sarawak, UNIMAS
2009
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/6528/ http://ir.unimas.my/id/eprint/6528/1/IMAGE%20QUALITY%20ANALYSIS%2824%20pgs%29.pdf http://ir.unimas.my/id/eprint/6528/8/SHANKAR.pdf |
| _version_ | 1848835934590599168 |
|---|---|
| author | Shankar, Krishnan. |
| author_facet | Shankar, Krishnan. |
| author_sort | Shankar, Krishnan. |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | Image quality analysis is becoming more an
d more important in this digital age. The
main objective of image quality analysis is to study the quality of image
s
and
develop methods to efficiently and swiftly determine the quality of images.
This
project aims to study subjective and obj
e
ctive assessm
ent methods of image quality
as well as to draw correlations between each objective assessment and the subjective
assessment.
Three objective assessment methods were used in this project, the
Quality Index algorithm developed by Zhou Wang
and Alan C. B
ovik
, the
Peak
Signal
-
to
-
Noise Ratio (
PSNR
)
Bl
ock
-
Set, and the
Mean Squared Error (
MSE
)
calculating algorithm.
By doing so, a better understanding of what is actually
required to develop an efficient image quality assessment method was gained. The
resulting da
ta also indicated what type of objective assessment was most suitable for
which type of impairment imposed upon an image. Finally, the conclusions of this
study were used to develop a prototype of a neural network based image quality
assessment method that
could be further enhanced as part of a further study to
eve
ntually develop an objective image quality analysis method that has a higher
correlation to the subjective assessment method compared to the other objective
assessment methods employed throughout
this project. |
| first_indexed | 2025-11-15T06:15:46Z |
| format | Final Year Project Report / IMRAD |
| id | unimas-6528 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T06:15:46Z |
| publishDate | 2009 |
| publisher | Universiti Malaysia Sarawak, UNIMAS |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-65282024-02-16T07:13:48Z http://ir.unimas.my/id/eprint/6528/ Image quality analysis Shankar, Krishnan. T Technology (General) TK Electrical engineering. Electronics Nuclear engineering Image quality analysis is becoming more an d more important in this digital age. The main objective of image quality analysis is to study the quality of image s and develop methods to efficiently and swiftly determine the quality of images. This project aims to study subjective and obj e ctive assessm ent methods of image quality as well as to draw correlations between each objective assessment and the subjective assessment. Three objective assessment methods were used in this project, the Quality Index algorithm developed by Zhou Wang and Alan C. B ovik , the Peak Signal - to - Noise Ratio ( PSNR ) Bl ock - Set, and the Mean Squared Error ( MSE ) calculating algorithm. By doing so, a better understanding of what is actually required to develop an efficient image quality assessment method was gained. The resulting da ta also indicated what type of objective assessment was most suitable for which type of impairment imposed upon an image. Finally, the conclusions of this study were used to develop a prototype of a neural network based image quality assessment method that could be further enhanced as part of a further study to eve ntually develop an objective image quality analysis method that has a higher correlation to the subjective assessment method compared to the other objective assessment methods employed throughout this project. Universiti Malaysia Sarawak, UNIMAS 2009 Final Year Project Report / IMRAD NonPeerReviewed text en http://ir.unimas.my/id/eprint/6528/1/IMAGE%20QUALITY%20ANALYSIS%2824%20pgs%29.pdf text en http://ir.unimas.my/id/eprint/6528/8/SHANKAR.pdf Shankar, Krishnan. (2009) Image quality analysis. [Final Year Project Report / IMRAD] (Unpublished) |
| spellingShingle | T Technology (General) TK Electrical engineering. Electronics Nuclear engineering Shankar, Krishnan. Image quality analysis |
| title | Image quality analysis |
| title_full | Image quality analysis |
| title_fullStr | Image quality analysis |
| title_full_unstemmed | Image quality analysis |
| title_short | Image quality analysis |
| title_sort | image quality analysis |
| topic | T Technology (General) TK Electrical engineering. Electronics Nuclear engineering |
| url | http://ir.unimas.my/id/eprint/6528/ http://ir.unimas.my/id/eprint/6528/1/IMAGE%20QUALITY%20ANALYSIS%2824%20pgs%29.pdf http://ir.unimas.my/id/eprint/6528/8/SHANKAR.pdf |