TY - JOUR
T1 - A learning-based approach to image demosaicking with spatial autocorrelation analysis
AU - Choi, Min Kook
AU - Joo, Chan
AU - Lee, Hyun Gyu
AU - Lee, Sang Chul
N1 - Publisher Copyright:
© 2016 Society for Imaging Science and Technology.
PY - 2016
Y1 - 2016
N2 - We introduce a two stage image demosaicking method for Bayer color filter array (CFA) images. Pixel interpolation using a Bayesian and/or SVM classifier is followed by renegotiation of the interpolated image with an auto-correlation function (ACF), which is applied to the distribution of edge strengths at each pixel of the interpolated image. This second stage can also be used to postprocess images produced by other demosaicking methods. Experimental results obtained with the Kodak PhotoCD benchmark show that our method shows enhanced edge and texture details and when compared with three other methods.
AB - We introduce a two stage image demosaicking method for Bayer color filter array (CFA) images. Pixel interpolation using a Bayesian and/or SVM classifier is followed by renegotiation of the interpolated image with an auto-correlation function (ACF), which is applied to the distribution of edge strengths at each pixel of the interpolated image. This second stage can also be used to postprocess images produced by other demosaicking methods. Experimental results obtained with the Kodak PhotoCD benchmark show that our method shows enhanced edge and texture details and when compared with three other methods.
UR - http://www.scopus.com/inward/record.url?scp=85087226798&partnerID=8YFLogxK
U2 - 10.2352/issn.2470-1173.2016.20.color-314
DO - 10.2352/issn.2470-1173.2016.20.color-314
M3 - Conference article
AN - SCOPUS:85087226798
SN - 2470-1173
JO - IS and T International Symposium on Electronic Imaging Science and Technology
JF - IS and T International Symposium on Electronic Imaging Science and Technology
T2 - Color Imaging XXI: Displaying, Processing, Hardcopy, and Applications 2016
Y2 - 14 February 2016 through 18 February 2016
ER -