We present a graph-based image processing algorithm using fast iterative bilateral filters. The computation of bilateral filters is accelerated with fixation of the coefficients during iterations and their approximate decomposition further speeds up the computation. We show that this fixed-coefficient iterative bilateral filter is an alternative solver for optimization problems in graph-based data analyses and apply its fast algorithm to graph-based image processing tasks. Performance of the present algorithm is demonstrated with experiments of contrast enhancement and smoothing of images using cross bilateral filters, in addition to semi-supervised image segmentation and colorization of monochromatic images. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Jian, C., Inoue, K., Hara, K., & Urahama, K. (2009). Fixed-coefficient iterative bilateral filters for graph-based image processing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5414 LNCS, pp. 473–484). https://doi.org/10.1007/978-3-540-92957-4_41
Mendeley helps you to discover research relevant for your work.