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The possibility of increasing the spatial resolution of video sequences is becoming extremely important in present-day multimedia systems. In this sense, super-resolution represents a smart way to obtain high-resolution video sequences from a finite set of low-resolution video frames. This set of low-resolution images must be obtained under different capture conditions of the image, from different spatial positions and/or from different cameras - this being the super-resolution paradigm, which is one of the fundamental challenges of sensor fusion. However, the vast computational cost associated with common super-resolution techniques jeopardizes their usefulness for real-time consumer applications. To alleviate this drawback, an implementation of a proprietary super-resolution algorithm mapped onto a hardware platform based on a digital signal processor (DSP) is presented in this paper. The results obtained show that, after an incremental optimization procedure, we are able to obtain super-resolved CIF video sequences (352 Ã 288 pixels) at 38 frames per second.
Date of Publication: November 2009