Inheritance, Subversion and Transcendence—Computational Photography

Xu Shukui, Zhang Jun, Tu Dan, and Li Guohui

Journal of Computer Research and Development > 2012 > 49(1): 128-143.

Xu Shukui, Zhang Jun, Tu Dan, and Li Guohui. Inheritance, Subversion and Transcendence—Computational Photography[J]. Journal of Computer Research and Development, 2012, 49(1): 128-143.

Citation:

Xu Shukui, Zhang Jun, Tu Dan, and Li Guohui. Inheritance, Subversion and Transcendence—Computational Photography[J]. Journal of Computer Research and Development, 2012, 49(1): 128-143.

Citation:

Xu Shukui, Zhang Jun, Tu Dan, and Li Guohui. Inheritance, Subversion and Transcendence—Computational Photography[J]. Journal of Computer Research and Development, 2012, 49(1): 128-143.

PDF (10741 KB)

Inheritance, Subversion and Transcendence—Computational Photography

Xu Shukui, Zhang Jun, Tu Dan, and Li Guohui

(College of Information System and Management, National University of Defense Technology, Changsha 410073)

More Information

Published Date: January 14, 2012

Graphical Abstract

Abstract

Abstract

Computational photography is an integrative technology which combines the computer and software technology with modern sensors and modern optics to create new imaging systems and image applications. In succession on the basis of existing photography, computational photography improves the components, workflow and even the principle of photography to break out of the limitation of traditional photography. It becomes a new revolution of photography. Computational photography is a cross-research area of many disciplines which can solve a problem through different perspectives and approaches. To fully understand this new area, computational photography is classified to computational scenes, computational optics, computational sensors and computational processing. In each subclass, some hot issues and typical projects are introduced. Finally, the existing circumstances of computational photography and trend in development are discussed.
- computational photography,
- computational scenes,
- computational optics,
- computational sensors,
- computational processing,
- image deblurring,
- high dynamic range,
- light field

FullText(HTML)

References (0)

[1]	Fan Wei, Liu Yong. Social Network Information Diffusion Prediction Based on Spatial-Temporal Transformer[J]. Journal of Computer Research and Development, 2022, 59(8): 1757-1769. DOI: 10.7544/issn1000-1239.20220064
[2]	Cao Jiuxin, Gao Qingqing, Xia Rongqing, Liu Weijia, Zhu Xuelin, Liu Bo. Information Propagation Prediction and Specific Information Suppression in Social Networks[J]. Journal of Computer Research and Development, 2021, 58(7): 1490-1503. DOI: 10.7544/issn1000-1239.2021.20200809
[3]	Xu Mingda, Zhang Zike, Xu Xiaoke. Research on Spreading Mechanism of False Information in Social Networks by Motif Degree[J]. Journal of Computer Research and Development, 2021, 58(7): 1425-1435. DOI: 10.7544/issn1000-1239.2021.20200806
[4]	Li Yingying, Ma Shuai, Jiang Haoyi, Liu Zhe, Hu Chunming, Li Xiong. An Approach for Storytelling by Correlating Events from Social Networks[J]. Journal of Computer Research and Development, 2018, 55(9): 1972-1986. DOI: 10.7544/issn1000-1239.2018.20180155
[5]	Liao Guoqiong, Jiang Shan, Zhou Zhiheng, Wan Changxuan. Dual Fine-Granularity POI Recommendation on Location-Based Social Networks[J]. Journal of Computer Research and Development, 2017, 54(11): 2600-2610. DOI: 10.7544/issn1000-1239.2017.20160502
[6]	Tan Zhenhua, Shi Yingcheng, Shi Nanxiang, Yang Guangming, Wang Xingwei. Rumor Propagation Analysis Model Inspired by Gravity Theory for Online Social Networks[J]. Journal of Computer Research and Development, 2017, 54(11): 2586-2599. DOI: 10.7544/issn1000-1239.2017.20160434
[7]	Wang Zhenwen, Xiao Weidong, and Tan Wentang. Classification in Networked Data Based on the Probability Generative Model[J]. Journal of Computer Research and Development, 2013, 50(12): 2642-2650.
[8]	Tan Wentang, Wang Zhenwen, Yin Fengjing, Ge Bin, and Xiao Weidong. A Partial Comparative Cross Collections LDA Model[J]. Journal of Computer Research and Development, 2013, 50(9): 1943-1953.
[9]	Guo Qiaojin, Li Ning, Yang Yubin, and Wu Gangshan. LDA-CRF: Object Detection Based on Graphical Model[J]. Journal of Computer Research and Development, 2012, 49(11): 2296-2304.
[10]	Li Zhi, Li Qianmu, Zhang Hong, Liu Fengyu. Closely Social Circuit Based Routing in Social Delay Tolerant Networks[J]. Journal of Computer Research and Development, 2012, 49(6): 1185-1195.