KEYWORDS: Mobile devices, Digital signal processing, Digital filtering, Wavelets, Linear filtering, Signal processing, Electronic filtering, Motion estimation, Wigner distribution functions, Filtering (signal processing)
Motion estimation (ME) is the most time consuming part in contemporary video compression algorithms and standards. In recent years, certain transform domain "phase-correlation" ME algorithms based on Complex-valued Wavelet Transforms have been developed to achieve lower complexity than the previous approaches.
In the present paper we describe an implementation of the basic phase-correlation ME techniques on a fixed-point dual-core processor architecture such as the TI OMAP one. We aim at achieving low computational complexity and algorithm stability without affecting the estimation accuracy.
The first stage of our ME algorithm is a multiscale complex-valued transform based on all-pass filters. We have developed wave digital filter (WDF) structures to ensure better performance and higher robustness in fixed-point arithmetic environments. For higher efficiency the structures utilize some of the dedicated filtering instructions present in the 'C5510 DSP part of the dual-core processor.
The calculation of motion vectors is performed using maximum phase-correlation criteria. Minimum subband squared difference is estimated for every subband level of the decomposition. To minimize the number of real-time computations we have adapted this algorithm to the functionality of the hardware extensions present in the 'C5510.
We consider our approach quite promising for realizing video coding standards on mobile devices, as many of them utilize fixed-point DSP architectures.