MARC details
| 000 -LEADER |
|---|
| fixed length control field |
05114ntm a2200337 i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
MY-KuUP |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20260525171913.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS |
|---|
| fixed length control field |
t||||fr|||| 000 0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
|---|
| fixed length control field |
ta |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
260525t20252025my a|||fr|||| 000 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
THE0010528 (Local) |
| Qualifying information |
Hardback |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
UMPSA |
| Language of cataloging |
eng |
| Transcribing agency |
UMPSA |
| Description conventions |
rda |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
|---|
| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
FTKPM .K36 2025 r Thesis |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Kamil Zakwan Bin Mohd Azmi, |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Development of underwater image contrast and color enhancement methods through optimization algorithm / |
| Statement of responsibility, etc. |
Kamil Zakwan Bin Mohd Azmi |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Kuantan, Pahang : |
| Name of producer, publisher, distributor, manufacturer |
UMPSA , |
| Date of production, publication, distribution, manufacture, or copyright notice |
2025 |
| 264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Date of production, publication, distribution, manufacture, or copyright notice |
© 2025 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xiv, 159 pages : |
| Other physical details |
illustrations ; |
| Dimensions |
30 cm. + |
| Accompanying material |
1 CD-ROM. |
| 336 ## - CONTENT TYPE |
|---|
| Source |
rdacontent |
| Content type term |
text |
| 337 ## - MEDIA TYPE |
|---|
| Source |
rdamedia |
| Media type term |
unmediated |
| 338 ## - CARRIER TYPE |
|---|
| Source |
rdacarrier |
| Carrier type term |
volume |
| 347 ## - DIGITAL FILE CHARACTERISTICS |
|---|
| Source |
rda |
| File type |
text file |
| Encoding format |
PDF |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Faculty of Manufacturing & Mechatronics Engineering Technology |
| 502 ## - DISSERTATION NOTE |
|---|
| Dissertation note |
Thesis (Doctor of Philosophy) -- Universiti Malaysia Pahang - 2025 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references |
| 520 3# - SUMMARY, ETC. |
|---|
| Summary, etc. |
Improving underwater images is one of the important prerequisites for researchers to explore the ocean, use underwater resources and develop underwater technology. Poor image quality ruins the accuracy of image processing applications. The shapes and colors of underwater objects are extremely difficult to be analyzed accurately due to the phenomenon of color absorption and light scattering. These problems limit the extraction of useful information that can be obtained from underwater images. These undesirable problems need to be addressed thoroughly, causing the underwater image enhancement is an important field to be investigated. Image enhancement techniques offer an effective solution, not only for a better visual experience but also enhance the reliability and robustness of image processing systems to analyze and process the images. There are various underwater image enhancement techniques that have been proposed to address these issues. However, most of these methods inadequately reduce underwater color cast and make a significant improvement to image contrast. The stretching process may become ineffective as the image histogram could be only stretched for a small range of intensity levels. Worst case scenario, the original histogram limits already hit the minimum and maximum dynamic range, resulting in no stretching process and no improvement could be done. Apart from the above-mentioned problems, it is observed that some underwater images are too dark, causing difficulty in interpreting the physical appearance of an object especially when the underwater object is located far away from the camera. In this thesis, three new methods have been proposed to improve the quality of underwater images, namely, swarm-intelligence-based underwater image color enhancement (SUCE), natural-based underwater image color enhancement (NUCE), and intensity-randomized-based underwater image contrast enhancement (IRUCE). The major contribution of SUCE is the reduction of color cast. The adapted gain factors are computed to compensate for the attenuation of minimum color channel, thus reducing unwanted blue-green color cast significantly. Meanwhile, NUCE focuses on improvement of image brightness. Through the incorporation of swarm-intelligence algorithm, the mean intensity values of inferior color channels are adjusted to be closed to the mean intensity value of superior color channel. On the other hand, IRUCE focuses on enhancement of image contrast. An alternative approach of histogram modification has been proposed to overcome the limited stretching issue of conventional global histogram stretching called as intensity-randomized technique. This method is developed to ensure that image intensity is properly distributed across all intensity levels. This technique is designed to fuse between under-enhanced and over-enhanced images. By utilizing the random values which are drawn from normal distribution, the image intensity is well-distributed across all intensity levels. The effectiveness of these proposed methods are tested with 300 underwater images and the results are compared to the other state-of-the-art methods. The results show that these proposed methods can improve underwater image quality significantly, while outperforms the other methods. The results show that IRUCE achieved the best performance with entropy = 7.787, AveGrad = 10.316, Sobel Count = 36913, and UIQM = 1.590, confirming that the proposed algorithms significantly improve underwater image quality and outperform existing methods. Beyond academic contributions, the findings offer practical impacts for real-world applications such as marine biology research, underwater exploration, search-and-rescue operations, and industrial inspections, where clearer images are critical for accurate decision-making and operational success. |
| 610 20 - SUBJECT ADDED ENTRY--CORPORATE NAME |
|---|
| Corporate name or jurisdiction name as entry element |
Faculty of Manufacturing & Mechatronics Engineering Technology |
| General subdivision |
Dissertations |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Universities and colleges |
| General subdivision |
Dissertations |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Theses |
| General subdivision |
Dissertations |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Thesis |