Computational Imaging and Automated Identification for Aqueous Environments

Nicholas Loomis, Ph.D., 2011
Cabell Davis, Advisor

Sampling the vast volumes of the ocean requires tools capable of observing from a distance while retaining detail necessary for biology and ecology, ideal for optical methods. Algorithms that work with existing SeaBED AUV imagery are developed, including habitat classi…cation with bag-of-words models and multi-stage boosting for rock…sh detection. Methods for extracting images of …fish from videos of longline operations are demonstrated.

A prototype digital holographic imaging device is designed and tested for quantitative in situ microscale imaging. Theory to support the device is developed, including particle noise and the e¤ects of motion. A Wigner-domain model provides optimal settings and optical limits for spherical and planar holographic references.

Algorithms to extract the information from real-world digital holograms are created. Focus metrics are discussed, including a novel focus detector using local Zernike moments. Two methods for estimating lateral positions of objects in holograms without reconstruction are presented by extending a summation kernel to spherical references and using a local frequency signature from a Riesz transform. A new metric for quickly estimating object depths without reconstruction is proposed and tested. An example application, quantifying oil droplet size distributions in an underwater plume, demonstrates the e¢ cacy of the prototype and algorithms.