지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 중앙대학교 영상콘텐츠융합연구소 TECHART: Journal of Arts and Imaging Science TECHART: Journal of Arts and Imaging Science Vol.1 No.1
- 발행연도
- 2014.2
- 수록면
- 55 - 59 (5page)
- DOI
- 10.15323/jais.2014.02.1.1.55
이용수
초록· 키워드
오류제보하기
In this paper, we present a spatially adaptive histogram equalization method for generating a ghost-free high dynamic range (HDR) image using a single input image. Existing multiple input-based HDR methods fuse multiple low dynamic range (LDR) images, acquired using different exposures. However, these methods work only under the assumption that neither global nor local motions exists in between the LDR images. To overcome such an unrealistic constraint, we generate two LDR images from a single input image. To generate LDR images with appropriate exposures, we divide the entire intensity range into multiple sub-ranges using histogram quantization and separately perform histogram equalization in each sub-range. Thus, we can acquire a set of differently exposed LDR images of the same scene, which are then fused to generate a ghost-free HDR image. The major contribution of this work is twofold: (i) a novel estimation method for providing optimal sub-ranges of intensity using histogram quantization, which (ii) requires no additional hardware for generating multiple LDR images. Because the proposed method uses a set of optimally self-generated LDR images, it is inherently free of ghost artifacts and can provide a ghost-free HDR function for low-cost, lightweight imaging devices, such as mobile phones and compact cameras.
목차
Abstract
1. Introduction
2. Spatial Adaptive Equalization of Quantized Histogram
3. Experimental Results
4. Conclusion
References
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UCI(KEPA) : I410-ECN-0101-2015-680-001306695