3D Fourier ghost imaging via semi-calibrated photometric stereo.

We achieved three-dimensional (3D) computational ghost imaging with multiple photoresistors serving as single-pixel detectors using the semi-calibrated lighting approach. We performed imaging in the spatial frequency domain by having each photoresistor obtain the Fourier spectrum of the scene at a low spectral coverage ratio of 5%. To retrieve a depth map of a scene, we inverted, apodized, and applied semi-calibrated photometric stereo (SCPS) to the spectra.

Digital cleaning and "dirt" layer visualization of an oil painting.

We demonstrate a new digital cleaning technique which uses a neural network that is trained to learn the transformation from dirty to clean segments of a painting image. The inputs and outputs of the network are pixels belonging to dirty and clean segments found in Fernando Amorsolo's Malacañang by the River. After digital cleaning we visualize the painting's discoloration by assuming it to be a transmission filter superimposed on the clean painting.

Automated benthic counting of living and non-living components in Ngedarrak Reef, Palau via subsurface underwater video.

We introduce an automated benthic counting system in application for rapid reef assessment that utilizes computer vision on subsurface underwater reef video. Video acquisition was executed by lowering a submersible bullet-type camera from a motor boat while moving across the reef area. A GPS and echo sounder were linked to the video recorder to record bathymetry and location points.

Rapid subsurface detection of nanoscale defects in live microprocessors by functional infrared emission spectral microscopy.

We demonstrate the rapid and nondestructive detection of subsurface nanometer-size defects in 90 nm technology live microprocessors with a new technique called functional infrared emission spectral microscopy. Broken, leaky, and good transistors with similar photoemission images are identified from each other by their different emission spectra that are calculated as linear combinations of weighted basis spectra. The basis spectra are derived from a spectral library by principal component analysis.

Classification of coral reef images from underwater video using neural networks.

We use a feedforward backpropagation neural network to classify close-up images of coral reef components into three benthic categories: living coral, dead coral and sand. We have achieved a success rate of 86.5% (false positive = 6.

Fluorescence spectrum estimation using multiple color images and minimum negativity constraint.

An inexpensive method to convert a microscope into an imaging spectrometer is presented. Unlike current microscope-based spectrometers which use specialized optics or scanning mechanisms, our system only requires at most two image captures with a 3-chip CCD camera and a lightly-tinted color filter to output the color signal of a sample at each pixel. Basis spectra are obtained by principal components analysis applied to an ensemble of color signals of commercially-available dyes observed with different dichroic mirrors.