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AUTOMATIC IMAGE AND VIDEO ENHANCEMENT
WITH APPLICATION TO VISUALLY IMPAIRED PEOPLE
by
Anustup Kumar Choudhury
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(COMPUTER SCIENCE)
August 2012
Copyright 2012 Anustup Kumar Choudhury
Object Description
| Title | Automatic image and video enhancement with application to visually impaired people |
| Author | Choudhury, Anustup Kumar Atanu |
| Author email | achoudhu@usc.edu;stup.anu@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Computer Science |
| School | Viterbi School of Engineering |
| Date defended/completed | 2012-04-25 |
| Date submitted | 2012-07-15 |
| Date approved | 2012-07-16 |
| Restricted until | 2012-07-16 |
| Date published | 2012-07-16 |
| Advisor (committee chair) |
Medioni, Gerard G. Medioni, Gérard G. |
| Advisor (committee member) |
Tjan, Bosco S. Ghosh, Abhijeet |
| Abstract | Images/videos may have poor visual quality due to the relatively low dynamic range of capture/display devices as compared to the human visual system or poor lighting conditions or the lack of experience of people capturing them. We are exploring techniques to perform automatic enhancement of images and videos. The goal is to produce a better visual experience for all viewers. Another motivation is to improve perception for visually impaired patients, in particular, people suffering from Age-related Macular Degeneration. In order to address these problems, we have developed novel techniques for contrast and sharpness enhancement of images and videos. ❧ Our color contrast enhancement technique is inspired from the Retinex theory. We use denoising techniques to estimate the illumination component of the image, while preserving color and white balance. We then enhance only the illumination component using mapping functions. These enhancement parameters are estimated automatically. This enhanced illumination is then combined with the original reflectance to obtain enhanced images with better contrast. ❧ For sharpness enhancement, we use a novel approach based on a hierarchical framework using edge-preserving Non-local means filter. The hierarchical framework is constructed from a single image using a modified version of Laplacian pyramid. We also introduce a new measure to quantify sharpness quality, which allows us to automatically set parameters in order to achieve a preferred sharpness enhancement. ❧ Finally, we propose a novel method based on modularity optimization to perform temporally consistent and robust enhancement of videos. A key aspect of our processes is that it is fully automatic. Our method detects scene changes `on-the-fly' in a video. For every detected cluster, we find a key frame that is most representative of other frames in the sequence and estimate enhancement parameters for only the key frame. We then enhance all frames in that cluster using these enhancement parameters, thus making our method robust. ❧ We compare our enhancement results with existing state-of-the-art approaches and commercial packages and show noticeable improvements. Our image enhancements do not suffer from halo effects, color artifacts, and color shifts; our video enhancement is temporally consistent and does not suffer from flash or flickering artifacts. Validation is challenging, as visual experience is intrinsically subjective. We have conducted extensive tests on real viewers (both normally sighted and simulated visually impaired), and provide a statistical measure of improvement in terms of preference. |
| Keyword | color contrast enhancement; human validation; image enhancement; sharpness enhancement; video enhancement; visually impaired people |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m |
| Contributing entity | University of Southern California |
| Rights | Choudhury, Anustup Kumar Atanu |
| Physical access | The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given. |
| Repository name | University of Southern California Digital Library |
| Repository address | USC Digital Library, University of Southern California, University Park Campus MC 7002, 106 University Village, Los Angeles, California 90089-7002, USA |
| Repository email | cisadmin@lib.usc.edu |
| Archival file | uscthesesreloadpub_Volume4/etd-ChoudhuryA-957.pdf |
Description
| Title | Page 1 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | AUTOMATIC IMAGE AND VIDEO ENHANCEMENT WITH APPLICATION TO VISUALLY IMPAIRED PEOPLE by Anustup Kumar Choudhury A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (COMPUTER SCIENCE) August 2012 Copyright 2012 Anustup Kumar Choudhury |
