Authors:
Patrik Goorts
;
Sammy Rogmans
and
Philippe Bekaert
Affiliation:
Hasselt University, Belgium
Keyword(s):
Demosaicing, Bayer, Finite Impulse Response Filtering, GPU, CUDA.
Related
Ontology
Subjects/Areas/Topics:
Design and Implementation of Signal Processing Systems
;
Image and Video Processing, Compression and Segmentation
;
Multimedia
;
Multimedia Signal Processing
;
Multimedia Systems and Applications
;
Sensors and Multimedia
;
Telecommunications
Abstract:
In this paper, we investigate demosaicing of raw camera images on parallel architectures using CUDA. To generate high-quality results, we use the method of Malvar et al., which incorporates the gradient for edgesensing demosaicing. The method can be implemented as a collection of finite impulse response filters, which can easily be mapped to a parallel architecture. We investigated different trade-offs between memory operations and processor occupation to acquire maximum performance, and found a clear difference in optimization
principles between different GPU architecture designs. We show that trade-offs are still important and not straightforward when using systems with massive fast processors and slower memory.