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학술지 Quality Assessment of Images Projected Using Multiple Projectors
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저자
Muhammad Umer Kakli, Hassaan Saadat Qureshi, Muhammad Murtaza Khan, Rehan Hafiz, 조용주, 박운상
발행일
201506
출처
KSII Transactions on Internet and Information Systems, v.9 no.6, pp.2230-2250
ISSN
1976-7277
출판사
한국인터넷정보학회
DOI
https://dx.doi.org/10.3837/tiis.2015.06.015
협약과제
14ZR1100, 휴먼융합형 파노라마 기술 개발, 차지훈
초록
Multiple projectors with partially overlapping regions can be used to project a seamless image on a large projection surface. With the advent of high-resolution photography, such systems are gaining popularity. Experts set up such projection systems by subjectively identifying the types of errors induced by the system in the projected images and rectifying them by optimizing (correcting) the parameters associated with the system. This requires substantial time and effort, thus making it difficult to set up such systems. Moreover, comparing the performance of different multi-projector display (MPD) systems becomes difficult because of the subjective nature of evaluation. In this work, we present a framework to quantitatively determine the quality of an MPD system and any image projected using such a system. We have divided the quality assessment into geometric and photometric qualities. For geometric quality assessment, we use Feature Similarity Index (FSIM) and distance-based Scale Invariant Feature Transform (SIFT). For photometric quality assessment, we propose to use a measure incorporating Spectral Angle Mapper (SAM), Intensity Magnitude Ratio (IMR) and Perceptual Color Difference (?봂). We have tested the proposed framework and demonstrated that it provides an acceptable method for both quantitative evaluation of MPD systems and estimation of the perceptual quality of any image projected by them.
키워드
Geometric and photometric quality, Guantitative quality assessment, Multi-projector display
KSP 제안 키워드
Distance-based, Feature similarity, Geometric and photometric quality, Guantitative quality assessment, High-resolution, Multi-projector display, Perceptual Quality, Quality assessment(IQA), Set up, Similarity index, Spectral angle mapper