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Principles Of Optics Electromagnetic Theory Of Propagation Interference And Diffraction Of Light

IEEE Transactions on Pattern Analysis and Machine Intelligence

Course Description This is an advanced course in which we explore the field of Statistical Optics. Topics covered include such subjects as the statistical properties of natural (thermal) and laser light, spatial and temporal coherence, effects of partial coherence on optical imaging instruments, effects on imaging due to randomly inhomogeneous media, and a statistical treatment of the detection of light. Development of this more comprehensive model of the behavior of light draws upon the use of tools traditionally available to the electrical engineer, such as linear system theory and the theory of stochastic processes.

http://ieeexplore.ieee.org/iel5/3/23094/01073023.pdf

Statistical optics

Multiscale patch-based contrast measure for small infrared target detection

Robust human visual system (HVS) properties can effectively improve the infrared (IR) small target detection capabilities, such as detection rate, false alarm rate, speed, etc. However, current algorithms based on HVS usually improve one or two of the aforementioned detection capabilities while sacrificing the others. In this letter, a robust IR small target detection algorithm based on HVS is proposed to pursue good performance in detection rate, false alarm rate, and speed simultaneously. First, an HVS size-adaptation process is used, and the IR image after preprocessing is divided into subblocks to improve detection speed. Then, based on HVS contrast mechanism, the improved local contrast measure, which can improve detection rate and reduce false alarm rate, is proposed to calculate the saliency map, and a threshold operation along with a rapid traversal mechanism based on HVS attention shift mechanism is used to get the target subblocks quickly. Experimental results show the proposed algorithm has good robustness and efficiency for real IR small target detection applications.

A Robust Infrared Small Target Detection Algorithm Based on Human Visual System

An improved infrared dim and small target detection algorithm based on the contrast mechanism of human visual system

Recently introduced speckle correlations-based techniques enable noninvasive imaging of objects hidden behind scattering layers. In these techniques, the hidden object Fourier amplitude is retrieved from the scattered light autocorrelation, and the lost Fourier phase is recovered via iterative phase-retrieval algorithms, which suffer from convergence to wrong local minimums solutions and cannot solve ambiguities in object orientation. Here, inspired by notions used in astronomy, we experimentally demonstrate that in addition to Fourier amplitude, the object-phase information is naturally and inherently encoded in the scattered light bispectrum (the Fourier transform of triple correlation) and can also be extracted from a single high-resolution speckle pattern, based on which we present a single-shot imaging scheme to deterministically and unambiguously retrieve diffraction-limited images of objects hidden behind scattering layers.

Single-shot diffraction-limited imaging through scattering layers via bispectrum analysis.

We hereby proposed and experimentally demonstrated an active polarization imaging technique, based on wavelength selection, for seeing through highly turbid water where targets are always visually lost. The method was realized by making use of the dependence of light scattering on wavelength in turbid water. Red light illumination was selected to minimize scattering occurring in light propagation and to guarantee accurate estimation of degree of polarization. Experiments demonstrate its contribution to turn targets in highly turbid water from “undetectable” to “detectable.”

Deeply seeing through highly turbid water by active polarization imaging.

A procedure for the detection and removal of haze from dense hazy images has been proposed. It involves the analysis on the content of low-spatial-frequency information of a scene. The image contaminated by haze is decomposed into different spatial frequency layers by the wavelet transform, by which the hazy parts of the image are focused on the low-frequency components. A dehazing method combining both the airlight and direct transmission is employed to specially dehaze the low-frequency parts. The high-frequency parts are processed by a transfer function to enhance the clarity of the hazy image. Finally, a dehazed image with high clarity is obtained by image construction which employs the low- and high-frequency components. Experiments and analyses demonstrate the good performance of the scheme in terms of improving the contrast and clarity of hazy images. Particularly, it works well in improving the visual range of images captured in hazy weather conditions.

Xiaopeng Shao

Papers

An improved infrared dim and small target detection algorithm based on the contrast mechanism of human visual system

Single-shot diffraction-limited imaging through scattering layers via bispectrum analysis.

Deeply seeing through highly turbid water by active polarization imaging.

Polarimetric dehazing utilizing spatial frequency segregation of images.

Imaging through scattering layers exceeding memory effect range by exploiting prior information