Space-variant video compression and processing in digital holographic microscopy sensor networks with application to potable water monitoring

Abstract

Water-related diseases affect societies in all parts of the world. Online sensors are considered a solution to the problems associated with laboratory testing in potable water. One of the most active research areas of such online sensors has been within optics. Digital holographic microscopy (DHM) has the potential to rival state-of-the-art techniques such as advanced turbidity measurement. However, its use as an online sensor is limited by the large data requirements typical for digital holographic video. In this paper, we provide a solution that permits DHM to be applied to a whole class of online remote sensor networks, of which potable water analysis is one example. The designed sensors incorporate a novel space-variant quantization algorithm to preprocess each frame of a video sequence before transmission over a network. The system satisfies the generally accepted requirements of an online system: automated, near real-time, and operating in a real environment. To verify the effectiveness of the design, we implemented and evaluated it in an active potable water facility.