Residual Interpolation for Color Image Demosaicking

Algorithm Overview

Publications

Journals

Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking
Yusuke Monno, Daisuke Kiku, Masayuki Tanaka and Masatoshi Okutomi
Sensors, Vol.17, No.12, pp.2787-1-21, December, 2017. [PDF]
Matlab code , Version 1.0, December 7, 2017

Beyond Color Difference: Residual Interpolation for Color Image Demosaicking
Daisuke Kiku, Yusuke Monno, Masayuki Tanaka and Masatoshi Okutomi
IEEE Transactions on Image Processing (TIP), Vol.25, No.3, pp.1288-1300, March, 2016. [PDF]
Matlab code , Version 1.2, January 15, 2016

Conferences

Adaptive Residual Interpolation for Color Image Demosaicking
Yusuke Monno, Daisuke Kiku, Masayuki Tanaka and Masatoshi Okutomi
IEEE International Conference on Image Processing (ICIP), pp.3861-3865, 2015 [PDF, Poster]
Matlab code , Version 1, September 25, 2015

Minimized-Laplacian Residual Interpolation for Color Image Demosaicking
Daisuke Kiku, Yusuke Monno, Masayuki Tanaka and Masatoshi Okutomi
IS&T/SPIE Electronic Imaging (EI), Digital Photography X, Vol.9023, pp.90230L-1-8, 2014 [PDF]
Matlab code , Version 1, November 26, 2013

Residual Interpolation for Color Image Demosaicking
Daisuke Kiku, Yusuke Monno, Masayuki Tanaka and Masatoshi Okutomi
IEEE International Conference on Image Processing (ICIP), pp.2304-2308, 2013. [PDF, Poster]
Matlab code , Version 1.2, July 25, 2013

   *Note for errors in TIP and ICIP2015 papers: We noticed that we incorrectly evaluated the LSLC algorithm. The LSLC algorithm uses a self-trained filter for each image, but in our evaluation, we incorrectly used the filter trained for the first Kodak image (as the default setting) for all images including the images in the IMAX dataset. We deeply apologize to the authors of the LSLC algorithm and the readers for any inconveniences this may have caused.

Benchmark Results for IMAX and Kodak 30 Images

Evaluation code

Please see the Sensors 2017 paper for details.

Compared Algorithms

• AP: http://www.ece.lsu.edu/ipl/Software.html
• PCSD: http://www.ece.mcmaster.ca/~xwu/
• SA: http://www.csee.wvu.edu/~xinl/demo/demosaic.html
• AHD: http://issl.udayton.edu/index.php/software/
• DLMMSE: http://www4.comp.polyu.edu.hk/~cslzhang/papers.htm
• FD: http://lcavwww.epfl.ch/reproducible_research/VandewalleKAS07/
• HEID: http://web.ntnu.edu.tw/~scy/heid_demo.html
• VCD: http://www.eie.polyu.edu.hk/~enyhchan/mypubl-14.htm
• LPA: http://www.cs.tut.fi/~lasip/cfai/
• DFPD: http://www.danielemenon.netsons.org/pub/dfapd/dfapd.php
• WA: http://www.danielemenon.netsons.org/pub/dbwalc/dbwalc.php
• HPHD: http://isci.cn.nctu.edu.tw/video/Demo/
• SSD: http://demo.ipol.im/demo/bcms_self_similarity_driven_demosaicking/
• RAD: http://www.danielemenon.netsons.org/pub/rad2/rad2.php
• LSSC: https://lear.inrialpes.fr/people/mairal/software.html
• GBTF: https://sites.google.com/site/ibrahimepekkucuksen/publications
• OAP: http://lu.seas.harvard.edu/software/demosaicking-matlab-code-implementing-fast-demosaicking-algorithm-described-following
• IGD: http://www.eie.polyu.edu.hk/~enyhchan/mypubl-14.htm
• NAT: http://www4.comp.polyu.edu.hk/~cslzhang/CDM_Dataset.htm
• CS: http://demo.ipol.im/demo/g_demosaicking_with_contour_stencils/
• ESF: https://sites.google.com/site/ibrahimepekkucuksen/publications
• MSG: https://sites.google.com/site/ibrahimepekkucuksen/publications
• AICC: http://www.ipol.im/pub/pre/145/
• ECC: http://spjaiswal.student.ust.hk/color_demosaicing.html
• IRI: result images were provided by the authors
• DDR: http://www.vision.ee.ethz.ch/~timofter/
• FR: http://www.vision.ee.ethz.ch/~timofter/

Related Projects

Single-Sensor RGB-NIR Imaging: High-Quality System Design and Prototype Implementation
Yusuke Monno, Hayato Teranaka, Kazunori Yoshizaki, Masayuki Tanaka and Masatoshi Okutomi
IEEE Sensors Journal, vol.19, no.2, pp.497-507, January, 2019. [Project]

Intensity Guided Depth Upsampling by Residual Interpolation
Yosuke Konno, Yusuke Monno, Daisuke Kiku, Masayuki Tanaka and Masatoshi Okutomi
JSME/RMD International Conference on Advanced Mechatronics (ICAM), pp.1-2, 2015. [Project]

Multispectral Demosaicking with Novel Guide Image Generation and Residual Interpolation
Yusuke Monno, Daisuke Kiku, Sunao Kikuchi, Masayuki Tanaka and Masatoshi Okutomi
IEEE International Conference on Image Processing (ICIP), pp.645-649, 2014. [Project]

Links to Multispectral Demosaicking Projects

    TokyoTech 5-band Multispectral Image Dataset
    TokyoTech 31-band Multispectral Image Dataset
    TokyoTech 59-band Visible-NIR Hyperspectral Image Dataset