(A) study on contrast enhancement and quality assessment measure using contextual information = 문맥 정보를 이용한 대비 향상 및 화질 평가 측정 연구

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The study on the visual quality has been extensively conducted for a long time since it can affect the performance of various computer vision algorithms. As the demand for obtaining high-quality images increases, image-enhancing techniques have attracted much attention. Among the several methods, contrast enhancement (CE) algorithm is often used to improve the image quality since contrast is an important factor in the human perception of image quality. Moreover, to develop effective and well-designed CE methods, research is needed on how to accurately predict the quality of images. In other words, the image quality assessment (IQA) can more accurately validate the superiority of CE algorithm performance and can help in the development of better CE algorithms. Therefore, this dissertation explores the study on how to improve the contrast and how to well measure the contrast quality. First, we present an adaptive CE algorithm considering both preservation of the shape of a 1D histogram and statistical information on the gray-level differences between neighboring pixels obtained by a 2D histogram. Compared with several state-of-the-art enhancement algorithms, the proposed algorithm shows highly competitive performance. Second, we propose the objective metric which can precisely predict the perceptual quality of contrast-changed images using inter-pixel contextual information. Experimental results show that the proposed metric provides a more accurate prediction of human perception of contrast change than other metrics. We further extend the CE algorithm to infrared (IR) images by using the proposed ramp distribution-based bit conversion method.
Advisors
Kim, Changickresearcher김창익researcher
Description
한국과학기술원 :전기및전자공학부,
Publisher
한국과학기술원
Issue Date
2019
Identifier
325007
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 전기및전자공학부, 2019.2,[vi, 80 p. :]

Keywords

Image enhancement▼acontrast enhancement▼aimage quality assessment (IQA)▼acontextual information▼aconstrained optimization▼acontrast-changed images; 영상 개선▼a대비 향상▼a영상 품질 평가▼a문맥 정보▼a제한적 최적화▼a대비가 변화된 영상

URI
http://hdl.handle.net/10203/265166
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=842219&flag=dissertation
Appears in Collection
EE-Theses_Ph.D.(박사논문)
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