Super-resolution sharpening-demosaicking with spatially adaptive total-variation image regularization

6Citations
Citations of this article
2Readers
Mendeley users who have this article in their library.
Get full text

Abstract

We previously presented a demosaicking method that simultaneously removes image blurs caused by an optical low-pass filter used in a digital color camera with the Bayer's RGB color filter array. Our prototypal sharpening-demosaicking method restored only spatial frequency components lower than the Nyquist frequency corresponding to the mosaicking pattern, but it often produced ringing artifacts near color edges. To overcome this difficulty, this paper introduces the super-resolution into the prototypal method. First, we for mulate the recovery problem in the DFT domain, and then introduce the super-resolution by the total-variation (TV) image regularization into the sharpening-demosaicking approach. The TV-based super-resolution effectively demosaics sharp color images while preserving such image structures as intensity values are almost constant along edges, without producing ringing artifacts, but it tends to flatten signal variations excessively in texture image regions. To remedy the drawback, furthermore we introduce a spatially adaptive technique that controls the TV image regularization according to the saliency of color edges around a pixel. © Springer-Verlag Berlin Heidelberg 2005.

Cite

CITATION STYLE

APA

Saito, T., & Komatsu, T. (2005). Super-resolution sharpening-demosaicking with spatially adaptive total-variation image regularization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3767 LNCS, pp. 246–256). Springer Verlag. https://doi.org/10.1007/11581772_22

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free