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Sampling the vast volumes of the ocean requirestools capable of observing from a distance while retaining detailnecessary for biology and ecology, ideal for optical methods.Algorithms that work with existing SeaBED AUV imagery aredeveloped, including habitat classification with bag-of-wordsmodels and multi-stage boosting for rock sh detection. Methods forextracting images of sh from videos of long-line operations aredemonstrated. A prototype digital holographic imaging device isdesigned and tested for quantitative in situ microscale imaging.Theory to support the device is developed, including particle noiseand the effects of motion. A Wigner-domain model provides optimalsettings and optical limits for spherical and planar holographicreferences. Algorithms to extract the information from real-worlddigital holograms are created. Focus metrics are discussed,including a novel focus detector using local Zernike moments. Twomethods for estimating lateral positions of objects in hologramswithout reconstruction are presented by extending a summationkernel to spherical references and using a local frequencysignature from a Riesz transform. A new metric for quicklyestimating object depths without reconstruction is proposed andtested. An example application, quantifying oil droplet sizedistributions in an underwater plume, demonstrates the efficacy ofthe prototype and algorithms.

Computational imaging and automated identification for aqueous environments