Low precision global motion estimation for video compression - A generalized framework

Global motion estimation (GME) is a fundamental problem in video compression and has been one of the most complex algorithms in digital video processing. The efficiency of real-time video processing operations has an important impact on the cost and realizability of complex algorithms, such as global motion estimation. Most digital video processing is carried out with a precision of 8 bits per pixel, however there has always been interest in low-complexity algorithms. One way of achieving low complexity is through low precision, such as might be achieved by quantization of each pixel to a single bit. Previous approaches to one-bit motion estimation have achieved quantization through a combination of spatial filtering/averaging and threshold setting. In this paper we present a generalized framework for precision reduction in video compression. Motivated by this generalized framework, we show that bit-plane selection provides higher performance, with lower complexity, than conventional approaches to quantization.