Generalized framework for reduced precision global motion estimation between digital images
The efficiency of real-time digital image processing operations has an important impact on the cost and realizability of complex algorithms. Global motion estimation is an example of such a complex algorithm. Most digital image 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. Motivated by this framework, we show that bit-plane selection provides higher performance, with lower complexity, than conventional approaches to quantization.