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3 May 2011Closing the gap between software and hardware super-resolution
image reconstruction: provision of high-quality output
The ability of additional detail extraction offered by the super-resolution image reconstruction (SRIR) algorithms greatly
improves the results of the process of spatial images augmentation, leading, where possible, to significant objective
image quality enhancement expressed in the increase of peak-signal-to-noise ratio (PSNR). Nevertheless, the ability of
providing hardware implementations of fusion SRIR algorithms capable of producing satisfactory output quality with
real-time performance is still a challenge. In order to make the hardware implementation feasible a number of trade-offs
that compromise the outcome quality are needed.
In this work we tackle the problem of high resource requirements by using a non-iterative algorithm that facilitates
hardware implementation. The algorithm execution flow is presented and described. The algorithm output quality is
measured and compared with competitive solutions including interpolation and iterative SRIR implementations. The
tested iterative algorithms use frame-level motion estimation (ME), whereas the proposed algorithm relies on,
performance-wise better, block matching ME. The comparison shows that the proposed non-iterative algorithm offers
superior output quality for all tested sequences, while promising efficient hardware implementation able to match -at
least- the software implementations in terms of outcome quality.
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Tomasz Szydzik, Gustavo M. Callico, Antonio Nunez, "Closing the gap between software and hardware super-resolution image reconstruction: provision of high-quality output," Proc. SPIE 8067, VLSI Circuits and Systems V, 80670M (3 May 2011); https://doi.org/10.1117/12.888253