Two-dimensional image moments with respect to Zernike polynomials are defined, and it is shown how to construct an arbitrarily large number of independent, algebraic combinations of Zernike moments that are invariant to image translation, orientation, and size. This approach is contrasted with the usual method of moments. The general problem of two-dimensional pattern recognition and three-dimensional object recognition is discussed within this framework. A unique reconstruction of an image in either real space or Fourier space is given in terms of a finite number of moments. Examples of applications of the method are given. A coding scheme for image storage and retrieval is discussed.

Image analysis via the general theory of moments

Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the tissue physiology, morphology, and composition. This review paper presents an overview of the literature on medical hyperspectral imaging technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application.

https://www.spiedigitallibrary.org/journals/journal-of-biomedical-optics/volume-19/issue-1/010901/Medical-hyperspectral-imaging-a-review/10.1117/1.JBO.19.1.010901.pdf

Medical hyperspectral imaging: a review

This tutorial paper gives an introduction and overview of various topics related to airborne laser scanning (ALS) as used to measure range to and reflectance of objects on the earth surface. After a short introduction, the basic principles of laser, the two main classes, i.e., pulse and continuous-wave lasers, and relations with respect to time-of-flight, range, resolution, and precision are presented. The main laser components and the role of the laser wavelength, including eye safety considerations, are explained. Different scanning mechanisms and the integration of laser with GPS and INS for position and orientation determination are presented. The data processing chain for producing digital terrain and surface models is outlined. Finally, a short overview of applications is given.

Airborne laser scanning—an introduction and overview

Images of outdoor scenes captured in bad weather suffer from poor contrast. Under bad weather conditions, the light reaching a camera is severely scattered by the atmosphere. The resulting decay in contrast varies across the scene and is exponential in the depths of scene points. Therefore, traditional space invariant image processing techniques are not sufficient to remove weather effects from images. We present a physics-based model that describes the appearances of scenes in uniform bad weather conditions. Changes in intensities of scene points under different weather conditions provide simple constraints to detect depth discontinuities in the scene and also to compute scene structure. Then, a fast algorithm to restore scene contrast is presented. In contrast to previous techniques, our weather removal algorithm does not require any a priori scene structure, distributions of scene reflectances, or detailed knowledge about the particular weather condition. All the methods described in this paper are effective under a wide range of weather conditions including haze, mist, fog, and conditions arising due to other aerosols. Further, our methods can be applied to gray scale, RGB color, multispectral and even IR images. We also extend our techniques to restore contrast of scenes with moving objects, captured using a video camera.

/pdf/contrast-restoration-of-weather-degraded-images-orn61jh9qu.pdf

Contrast restoration of weather degraded images

Current vision systems are designed to perform in clear weather. Needless to say, in any outdoor application, there is no escape from “bad” weather. Ultimately, computer vision systems must include mechanisms that enable them to function (even if somewhat less reliably) in the presence of haze, fog, rain, hail and snow.

We begin by studying the visual manifestations of different weather conditions. For this, we draw on what is already known about atmospheric optics, and identify effects caused by bad weather that can be turned to our advantage. Since the atmosphere modulates the information carried from a scene point to the observer, it can be viewed as a mechanism of visual information coding. We exploit two fundamental scattering models and develop methods for recovering pertinent scene properties, such as three-dimensional structure, from one or two images taken under poor weather conditions.

Next, we model the chromatic effects of the atmospheric scattering and verify it for fog and haze. Based on this chromatic model we derive several geometric constraints on scene color changes caused by varying atmospheric conditions. Finally, using these constraints we develop algorithms for computing fog or haze color, depth segmentation, extracting three-dimensional structure, and recovering “clear day” scene colors, from two or more images taken under different but unknown weather conditions.

/pdf/vision-and-the-atmosphere-29oh2z55ig.pdf

Vision and the Atmosphere

: Contents: Radiation Theory, Artificial Sources, Natural Sources, Atmospheric Scattering, Atmospheric Absorption, Propagation Through Atmospheric Turbulence, Optical Materials, Optical Design, Optical Elements-Lenses and Mirrors, Optical-Mechanical Scanning Techniques and Devices, Detectors, Charge- Coupled Devices, Imaging tubes, Photographic Film, Cooling Systems, Detector- Associated Electronics, Reticle and Image Analyses, Displays, Imaging Systems, Radiometry, Warning Systems, Tracking Systems, Ranging, Communications, and Simulation Systems, Aerodynamic Influences on Infrared System Design, and Physical Constants and Conversion Factors.

The Infrared Handbook

The refractive indexes and their variations with temperature for silicon and germanium have been measured over the 95–298-K and 2.5–12-μm ranges. Data are given for the refractive index that are in reasonable agreement with those of previous investigators. For dn/dT the values are independent of wavelength and are approximately 1.5 × 10−4 (K)−1 and 4.0 × 10−4 (K)−1 for silicon and germanium, respectively.

Refractive indexes and temperature coefficients of germanium and silicon.

: Contents: Introduction; Radiation theory, Artificial sources; Targets; Backgrounds; Atmospheric phenomena; Optical components; Optical materials; Optics; Optical systems; Detectors; Detector cooling systems; Film; Preamplifiers and associated circuits; Optical frequency-response techniques; Spatial frequency filtering; Control systems; System design; Infrared measuring instruments; Spacecraft thermal design; Aerodynamic influences on infrared system design; Physical constants and conversion factors.

Handbook of military infrared technology

The infrared handbook

The concepts of BRDF (Bidirectional Reflectance Distribution Function) and BTDF (Bidirectional Transmittance Distribution Function) are defined and discussed as being the ratios of differential outputs of radiance divided by differential inputs of irradiance. Appropriate measurement arrangements and procedures are presented, and the problems are described that are involved in going from the differentials of theory to the finite quantities of measurement. Finally appropriate data reduction schemes are given for determining BRDF and BTDF from these measurements.

William L. Wolfe

Papers

The Infrared Handbook

Refractive indexes and temperature coefficients of germanium and silicon.

Handbook of military infrared technology

The infrared handbook

The Theory And Measurement Of Bidirectional Reflectance Distribution Function (Brdf) And Bidirectional Transmittance Distribution Function (BTDF)