Lev S. Dolin

Novel algorithm of processing optical coherence tomography images for differentiation of biological tissue pathologies

A numerical algorithm based on a small-angle approximation of the radiative transfer equation (RTE) is developed to reconstruct scattering characteristics of biological tissues from optical coherence tomography (OCT) images. According to the algorithm, biological tissue is considered to be a layered random medium with a set of scattering parameters in each layer: total scattering coefficient, variance of a small-angle scattering phase function, and probability of backscattering, which fully describe the OCT signal behavior versus probing depth. The reconstruction of the scattering parameters is performed by their variation to fit the experimental OCT signal by the theoretical one using a time-saving genetic algorithm. The proposed reconstruction procedure is tested on model media with known scattering parameters. The possibility to estimate scattering parameters from OCT images is studied for various regimes of OCT signal decay. The developed algorithm is applied to reconstruct optical characteristics of epithelium and stroma for normal cervical tissue and its pathologies, and the potential to distinguish between the types of pathological changes in epithelial tissue by its OCT images is demonstrated.

Determination of wind roughness characteristics based on an underwater image of the sea surface

The opportunities of diagnosing wind roughness with the help of underwater vision systems have been investigated. The model of the rough sea surface image observed from under water under conditions of natural illumination has been developed. It has been shown that the statistical processing of the image of a solar path which is formed as a result of light refraction at randomly irregular air-water interface allows one to define not only the slope variance and the curvature variance of the surface, but also the coefficient of spatial correlation of slopes. The algorithms for defining of characteristics of wind roughness on the basis of images of underwater solar path and the results of their testing using the data of numerical and natural experiments are given. It was found that waves of very small amplitude images with high contrast near borders of the Snell’s circle (the underwater image of the sky).

Effect of sea waves on the limiting resolution of aircraft oceanographic lidars

The effect of sea waves on the characteristics of bathymetric lidars is studied. The main effects responsible for the distortion of bathymetric information are discussed. The displacement of the sounding beam and its broadening in a horizontal plane, the statistical mean variation in the signal’s delay time, the variance of signal arrival times, and the increase in the duration of the received signal are evaluated. The calculations are performed allowing for the absorption and multiple scattering of light in water.

Model of an underwater imaging system with a complexly modulated illumination beam

The optical transfer functions of underwater imaging systems that use narrow beams modulated by a complex high-frequency signal to form an image are studied. Images of simple objects observed with the use of such systems are calculated. The image distortions caused by the interference of modulation waves are estimated, and a method for eliminating these distortions is proposed. The potential for improving the image quality through the application of complexly modulated illumination beams is demonstrated using explicit calculations.

Determination of the variance of rough water surface slopes by the distortion of Snell’s circle boundary

We studied the opportunities of diagnostic of the wind roughness by distortions of Snell’s circle boundary images, i.e., images of the sky observed from underwater through a rough water surface. Models of random realization and statistically average image of Snell’s circle which takes into account various condition of illumination (overcast sky, clear sky and isotropic distribution of sky radiance) have been developed. Formulas for definition of slope variance of the sea surface by distortion of Snell’s circle boundary for one-dimensional roughness have been received. Dependence of accuracy of definition of slope variance on time of image averaging, depth of receiver diving, wind speed, range of waves forming the roughness, have been analyzed by the method of computer modeling. It has been shown on the basis of numerical calculation and experimental data that waves with length from millimeters to meters can be shown in the image of Snell’s circle depending from depth of receiver diving, receiver resolution and water turbidity.

A lidar method for determining internal wave characteristics

An analytical model of lidar imaging of pycnoclinic internal waves (IWs) is developed. The IW image is shown to represent a superposition of two images: reflective and shadow. The former reflects perturbations in the profile of the light backscattering coefficient in the IW field, and the latter reflects perturbations in the optical thickness of the water layer, in which the IW disturbed the horizontal uniformity of optical characteristics. Algorithms for reconstructing the IW field from these images are proposed. It is shown that the shadow image, unlike the reflective one, is insensitive to fine details of the profiles of hydrooptical characteristics and can be used for determining IW parameters on the basis of very rough data on optical properties of water. The possibility of determining the mode composition as well as the lengths and amplitudes of IW modes is demonstrated by using the Barents Sea as an example and invoking actual and simultaneously measured profiles of the water density and light attenuation coefficient.

Water-scattered signal to compensate for the rough sea surface effect on bottom lidar imaging

We investigate the possibility of using the water-backscattered radiation from a bottom sounding airborne imaging light detection and ranging (lidar) system to determine the surface slope at the point where the laser beam intersects the surface. We show that the refraction angle of the beam can be determined using receivers whose sensitivities vary linearly over their field of view. Equations are derived to estimate the statistical mean and variance values of this refracted angle. We demonstrate that the proposed algorithm improves lidar imaging. Numerical examples with reference to typical marine conditions are given.

Influence of illumination conditions on the sea-bottom visibility

Statistical models of the useful and background signals forming an image of the sea bottom observed through a rough sea surface are constructed. The methods for estimating the signal-to-noise ratio in the image of the bottom with the test distribution of the reflectance are described. The dependence of the signal-to-noise ratio on observational conditions, in particular, on the mutual orientation of the directions of sighting, wind, and solar vertical, is analyzed. Recommendations on the choice of optimal conditions for bottom observations from airborne carriers are given.

On observing underwater objects through a wavy water surface: A new algorithm for image correction and laboratory experiment

The possibility of correcting refraction distortions in images of the sea bottom or an underwater object observed through a wavy water surface is studied. A fast-operating algorithm of recovering the “regular” image by its random realization and spatial distribution of surface slopes at the instant of observation has been proposed and approbated. A technique of determining surface slopes by the surface image with the following correction of the underwater object image based on the data about the surface slopes has been developed under conditions of a laboratory experiment.

Image transfer through rough sea surface: computer simulations

This paper is devoted to computer simulation of random realizations of bottom images. Simulations of random images are considered to be a straightforward way to predict bottom visibility under realistic conditions. A simplified version of a bottom imaging model using a fast simulation algorithm has been developed. Simulated results presented here allow the visual evaluation of image quality for different signal/noise ratio (SNR) values. We show how the simulation of random images can be used to predict bottom visibility over a variety of environmental conditions and also determine an optimal observation strategy.