Depth estimation using spectrally varying defocus blur

被引:2
|
作者
Ishihara, Shin [1 ]
Sulc, Antonin [2 ]
Sato, Imari [1 ,3 ]
机构
[1] Tokyo Inst Technol, Meguro Ku, 2-12-1 Ookayama, Tokyo 1528550, Japan
[2] Univ Konstanz, Univ Str 10, D-78474 Constance, Germany
[3] Natl Inst Informat, Chiyoda Ku, 2-1-2 Hitotsubashi, Tokyo 1018430, Japan
基金
日本学术振兴会;
关键词
CHROMATIC ABERRATION; PASSIVE DEPTH; SHAPE;
D O I
10.1364/JOSAA.422059
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
This paper proposes a method to estimate depth from a single multispectral image by using a lens property known as chromatic aberration. Chromatic aberration causes light passing through a lens to be refracted depending on the wavelength. The refraction causes the angle of rays to vary depending on their wavelength and a change in focal length, which leads to a defocus blur for different wavelengths. We propose a theory to recover a continuous depth map from the blur in a single multispectral image that includes chromatic aberration. The proposed method needs only a standard wide-aperture lens, which naturally exhibits chromatic aberration, and a multispectral camera. Moreover, we use a simple yet effective depth-of-field synthesis method to calculate the derivatives and obtain allin-focus images necessary to approximate spectral derivatives. We verified the effectiveness of the proposed method on various real-world scenes. (c) 2021 Optical Society of America
引用
收藏
页码:1140 / 1149
页数:10
相关论文
共 50 条
  • [1] Static Object Depth Estimation Using Defocus Blur Levels Features
    Rajabzadeh, Tayebeh
    Vahedian, Abedin
    Pourreza, Hamidreza
    2010 6TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS NETWORKING AND MOBILE COMPUTING (WICOM), 2010,
  • [2] SUPERPIXEL-BASED DEPTH MAP ESTIMATION USING DEFOCUS BLUR
    Mahmoudpour, Saeed
    Kim, Manbae
    2016 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2016, : 2613 - 2617
  • [3] Depth Recovery Using Defocus Blur at Infinity
    Lin, Huei-Yung
    Gu, Kai-Da
    19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6, 2008, : 1068 - 1071
  • [4] Blur Calibration for Depth from Defocus
    Mannan, Fahim
    Langer, Michael S.
    2016 13TH CONFERENCE ON COMPUTER AND ROBOT VISION (CRV), 2016, : 281 - 288
  • [5] Depth from motion and defocus blur
    Lin, Huei-Yung
    Chang, Chia-Hong
    OPTICAL ENGINEERING, 2006, 45 (12)
  • [6] DEPTH FROM SPECTRAL DEFOCUS BLUR
    Ishihara, Shin
    Sulc, Antonin
    Sato, Imari
    2019 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2019, : 1980 - 1984
  • [7] Depth Estimation Based on Defocus Blur Using a Single Image Taken by a Tilted Lens Optics Camera
    Taketomi, Yuzo
    Ikeoka, Hiroshi
    Hamamoto, Takayuki
    2013 INTERNATIONAL SYMPOSIUM ON INTELLIGENT SIGNAL PROCESSING AND COMMUNICATIONS SYSTEMS (ISPACS), 2013, : 403 - 408
  • [8] The utility of defocus blur in binocular depth perception
    Vishwanath, Dhanraj
    I-PERCEPTION, 2012, 3 (08): : 541 - 546
  • [9] Deep Depth from Defocus: How Can Defocus Blur Improve 3D Estimation Using Dense Neural Networks?
    Carvalho, Marcela
    Le Saux, Bertrand
    Trouve-Peloux, Pauline
    Almansa, Andres
    Champagnat, Frederic
    COMPUTER VISION - ECCV 2018 WORKSHOPS, PT I, 2019, 11129 : 307 - 323
  • [10] Depth recovery from motion and defocus blur
    Lin, Huei-Yung
    Chang, Chia-Hong
    IMAGE ANALYSIS AND RECOGNITION, PT 2, 2006, 4142 : 122 - 133