A fast, automatic camera image stabilization benchmarking scheme

While image stabilization(IS ) has become a default functionality for most digital cameras, there is a lack of automatic IS evaluation scheme. Most publicly known camera IS reviews either require human visual assessment or resort to some generic blur metric. The former is slow and inconsistent, and the latter may not be easily scalable with respect to resolution variation and exposure variation when comparing different cameras. We proposed a histogram based automatic IS evaluation scheme, which employs a white noise pattern as shooting target. It is able to produce accurate and consistent IS benchmarks in a very fast manner.