Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.
Super-resolution is a smart process capable of generating
images with a higher resolution than the resolution of the sensor
used to acquire the images. Due to this reason, it has acquired a
significant relevance within the medical community during the
last years, especially for those specialties closely related with
the medical imaging field. However, the super-resolution
algorithms used in this field are normally extremely complex
and thus, they tend to be slow and difficult to be implemented
in hardware. This paper proposes a new super-resolution
algorithm for video sequences that, while maintaining excellent
levels in the objective and subjective visual quality of the
processed images, presents a reduced computational cost due to
its non-iterative nature and the use of fast motion estimation
techniques. Additionally, the algorithm has been successfully
implemented in a low-cost hardware platform, which guarantees
the viability of the proposed solution for real-time biomedical
systems-on-chip.
