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Image Contrast Enhancement based on Histogram Equalization of Sub-images
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Dong-Yoon Kim | - |
| dc.contributor.author | Suvanov Sharof | - |
| dc.date.accessioned | 2018-11-08T08:21:32Z | - |
| dc.date.available | 2018-11-08T08:21:32Z | - |
| dc.date.issued | 2015-02 | - |
| dc.identifier.other | 19516 | - |
| dc.identifier.uri | https://dspace.ajou.ac.kr/handle/2018.oak/13035 | - |
| dc.description | 학위논문(석사)--아주대학교 일반대학원 :컴퓨터공학과,2015. 2 | - |
| dc.description.tableofcontents | Table of Contents ACKNOWLEDGEMENTS i Abstract ii Table of Contents iii List of Figures iv List of Tables v LIST OF ACRONYMS vi 1.Introduction 1 1.1 Objective of Research 2 1.2 Methodology of Research 2 1.3 Organization of the Thesis 3 2. Related Work 4 3. Proposed Scheme 6 3.1. Overview 6 3.2. Computation of Histogram Equalization 8 3.3. Computation of Image Contrast 10 4. Experimental results 11 4.1. Numerical comparison 11 4.2. Statistical comparison 14 4.3. Image quality comparison 20 5. Conclusion and Future Work 25 REFERENCES 26 | - |
| dc.language.iso | eng | - |
| dc.publisher | The Graduate School, Ajou University | - |
| dc.rights | 아주대학교 논문은 저작권에 의해 보호받습니다. | - |
| dc.title | Image Contrast Enhancement based on Histogram Equalization of Sub-images | - |
| dc.type | Thesis | - |
| dc.contributor.affiliation | 아주대학교 일반대학원 | - |
| dc.contributor.department | 일반대학원 컴퓨터공학과 | - |
| dc.date.awarded | 2015. 2 | - |
| dc.description.degree | Master | - |
| dc.identifier.localId | 695408 | - |
| dc.identifier.url | http://dcoll.ajou.ac.kr:9080/dcollection/jsp/common/DcLoOrgPer.jsp?sItemId=000000019516 | - |
| dc.subject.keyword | histogram equalization | - |
| dc.subject.keyword | contrast enhancement | - |
| dc.description.alternativeAbstract | Abstract This thesis presents a method to enhance the contrast of an image by applying histogram equalization to the sub-image. The histogram of the image was decomposed into parts with respect to the location of its peak. HE was run on the selected part of the image containing the peak intensity level while the other parts remained unchanged. Then, the equalized and unchanged parts of the histogram were combined into a single image. Having applied histogram equalization on the sub-images with various sizes on different locations, the images with the highest contrast value were chosen. According to the acquired results, histogram equalization was classified into seven groups by the size and location of the equalized part. Applying histogram equalization to the selected part of the image, where the peak is located, generated higher contrast. Qualitative and quantitative experimental results are shown. Key words: histogram equalization, contrast enhancement, image decomposition, image partition, sub-image. | - |
- Appears in Collections:
- Graduate School of Ajou University > Department of Computer Engineering > 3. Theses(Master)
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