Range image fusion for object reconstruction and modeling

Author(s):  
Xiaokun Li ◽  
W.G. Wee
Author(s):  
Guilherme Canarin Marcellino ◽  
Bernardo Cassimiro Fonseca de Oliveira ◽  
Vicente Borges ◽  
Tiago Loureiro Figaro da Costa Pinto

2017 ◽  
Vol 37 (4) ◽  
pp. 0410001
Author(s):  
都琳 Du Lin ◽  
孙华燕 Sun Huayan ◽  
王帅 Wang Shuai ◽  
高宇轩 Gao Yuxuan ◽  
齐莹莹 Qi Yingying

2010 ◽  
Vol 7 (4) ◽  
pp. 626-630 ◽  
Author(s):  
Hongxian Wang ◽  
Yinghui Quan ◽  
Mengdao Xing ◽  
Shouhong Zhang

2009 ◽  
Vol 11 (5) ◽  
pp. 631-637
Author(s):  
Na REN ◽  
Xuejun LIU ◽  
Changqing ZHU

2019 ◽  
Vol 5 (3) ◽  
pp. 32 ◽  
Author(s):  
Ioannis Merianos ◽  
Nikolaos Mitianoudis

Modern imaging applications have increased the demand for High-Definition Range (HDR) imaging. Nonetheless, HDR imaging is not easily available with low-cost imaging sensors, since their dynamic range is rather limited. A viable solution to HDR imaging via low-cost imaging sensors is the synthesis of multiple-exposure images. A low-cost sensor can capture the observed scene at multiple-exposure settings and an image-fusion algorithm can combine all these images to form an increased dynamic range image. In this work, two image-fusion methods are combined to tackle multiple-exposure fusion. The luminance channel is fused using the Mitianoudis and Stathaki (2008) method, while the color channels are combined using the method proposed by Mertens et al. (2007). The proposed fusion algorithm performs well without halo artifacts that exist in other state-of-the-art methods. This paper is an extension version of a conference, with more analysis on the derived method and more experimental results that confirm the validity of the method.


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