Title :
Improved hybrid demosaicing and color super-resolution implementation using quasi-Newton algorithms
Author :
Sorrentino, Diego A. ; Antoniou, Andreas
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Victoria, Victoria, BC
Abstract :
Super-resolution algorithms can be used to reconstruct a high-resolution high-quality image from a set of low-quality images. A novel hybrid demosaicing and color super-resolution approach proposed by Farsiu, Elad, and Milanfar relies on the minimization of a nonconvex multiterm objective function using a rudimentary fixed step-size steepest-descent approach. In this paper, we show that improved performance can be achieved by implementing this approach in terms of powerful quasi-Newton algorithms.
Keywords :
concave programming; image colour analysis; image reconstruction; image resolution; minimisation; color super-resolution implementation; hybrid demosaicing; image reconstruction; image resolution; nonconvex multiterm objective function minimization; quasiNewton algorithms; rudimentary fixed step-size steepest-descent approach; Additive noise; Color; Colored noise; Filtering; Image reconstruction; Image resolution; Image sensors; Layout; Sensor arrays; Sensor systems; Image processing; demosaicing; quasi-Newton algorithms; super-resolution;
Conference_Titel :
Electrical and Computer Engineering, 2009. CCECE '09. Canadian Conference on
Conference_Location :
St. John´s, NL
Print_ISBN :
978-1-4244-3509-8
Electronic_ISBN :
0840-7789
DOI :
10.1109/CCECE.2009.5090241