Complexity scalability algorithms are important for mobile consumer devices using MPEG video coding, because they offer a trade-off between picture quality and the embedded available computational performance. This paper presents a new scalable three-stage motion estimation technique, which includes preprocessing of frames in display order and approximation of motion-vector fields using multiple temporal references. A quality refinement of the approximation is added as an optional stage. Furthermore, we present a new scalable motion-estimation algorithm, based on simple edge detection, for integration into the above-mentioned new three-stage motion estimation technique. The complete system provides a flexible framework with a large scalability range in computational effort, resulting in an output quality that scales up smoothly with the number of operations spent on the motion estimation process. Experiments show a scalable computational effort from below one SAD (sum of absolute difference) computation per macroblock up to 15 SAD computations, resulting in a global variation of 7.4 dB PSNR in picture quality (with the "Stefan" sequence). In high-quality operation, the new algorithm is comparable to (or even outperforms) a full-search motion estimation with a search window of 32/spl times/32 pixels.
['Stephan Mietens', 'Christian Hentschel']
Computational-complexity scalable motion estimation for mobile MPEG encoding