Development of Robust and Efficient Image Enhancement Techniques / (Record no. 616111)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03380nam a22001697a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | NUST |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 621.382,CHA |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Chaudhry, Alina Majeed |
| 9 (RLIN) | 124459 |
| 245 ## - TITLE STATEMENT | |
| Title | Development of Robust and Efficient Image Enhancement Techniques / |
| Statement of responsibility, etc. | Alina Majeed Chaudhry |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Rawalpindi, |
| Name of publisher, distributor, etc. | MCS (NUST), |
| Date of publication, distribution, etc. | 2021 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 104 p |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Formatted contents note | A number of computer vision systems and applications require high resolution, visually<br/>enhanced images with high contrast and preserved color and detail information, as inputs.<br/>However, in reality, due to the camera sensor limitations and challenging and adverse imaging<br/>conditions, such as poor lighting or bad weather, the captured images may suffer from<br/>low contrast, reduced visibility, haze, distorted colors or low resolution. Therefore the images<br/>need to be enhanced before they can be used for various computer vision systems.<br/>Image enhancement techniques aim to improve the visual appearance of images, and make<br/>them suitable for human/machine perception, so that they can be used in their required image<br/>processing and computer vision applications, such as surveillance and security systems,<br/>target identification, scene analysis, medical image processing, satellite imagery and remote<br/>sensing.<br/>This thesis presents various image enhancement techniques from the perspective of resolution<br/>enhancement using super resolution and visibility enhancement using image dehazing.<br/>In this regard, five different image enhancement techniques focusing on resolution and visibility<br/>enhancement are presented.<br/>The first technique focuses on image resolution enhancement, in which compressive sensing<br/>through sparse representation, based on self example dictionary learning and guided filtering<br/>is used for super resolution of images. The effectiveness of the proposed methodology is<br/>verified through quantitative and visual analysis. The last four techniques target visibility enhancement<br/>of different types of hazy images including outdoor, underwater, satellite/aerial<br/>and low light images through various dehazing methodologies. The second technique is<br/>based on filtering, detail enhancement and contrast improvement for the visibility enhancement<br/>of underwater images with poor visibility. Visibility enhancement and dehazing of<br/>images using local Laplacian filtering and l0 gradient decomposition is proposed as the third<br/>enhancement technique. The fourth image visibility enhancement technique uses image decomposition,<br/>detail enhancement and fusion for dehazing of images. The fifth technique for<br/>visibility enhancement makes use of edge preserving image decomposition and application<br/>of different enhancement strategies on the basis of whether the image is a dark low light<br/>image, or a hazy image. The technique works well for low light, as well as underwater and<br/>outdoor hazy images. The presented techniques generate effectively dehazed, visually plausible<br/>images, with enhanced visibility, improved contrast and preserved image details.<br/>Visual and quantitative comparison of the presented techniques with existing state of the art techniques demonstrates the effectiveness of the proposed image enhancement methodologies. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | PhD Electrical Engineering Thesis |
| 9 (RLIN) | 133107 |
| 651 ## - SUBJECT ADDED ENTRY--GEOGRAPHIC NAME | |
| Geographic name | PhD EE Thesis |
| 9 (RLIN) | 133108 |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Supervised by Dr. Abdul Ghafoor. |
| 9 (RLIN) | 132894 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | |
| Koha item type | Thesis |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Permanent Location | Current Location | Shelving location | Date acquired | Total Checkouts | Full call number | Barcode | Date last seen | Price effective from | Koha item type | Public note |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Military College of Signals (MCS) | Military College of Signals (MCS) | Thesis | 02/07/2026 | 621.382,CHA | MCSPhD EE-17 | 02/07/2026 | 02/07/2026 | Thesis | Almirah No.68, Shelf No.6 |