To solve the problem of metamerism in the color reproduction process, various spectral reflectance reconstruction methods combined with neural network have been proposed in recent years. However, these methods are generally sensitive to initial values and can easily converge to local optimal solutions, especially on small data sets. In this paper, we propose a spectral reflectance reconstruction algorithm based on the Back Propagation Neural Network (BPNN) and an improved Sparrow Search Algorithm (SSA). In this algorithm, to solve the problem that BPNN is sensitive to initial values, we propose to use SSA to initialize BPNN, and we use the sine chaotic mapping to further improve the stability of the algorithm. In the experiment, we tested the proposed algorithm on the X-Rite ColorChecker Classic Mini Chart which contains 24 colors, the results show that the proposed algorithm has significantly better performance compared to other algorithms and moreover it can meet the needs of spectral reflectance reconstruction on small data sets. Code is avaible at https://github.com/LuraZhang/spectral-reflectance-reconsctuction.

Water detection is important for machine vision applications such as visual inspection and robot motion planning. In this paper, we propose an approach to per-pixel water detection on unknown surfaces with a hyperspectral image. Our proposed method is based on the water spectral characteristics: water is transparent for visible light but translucent/opaque for near-infrared light and therefore the apparent near-infrared spectral reflectance of a surface is smaller than the original one when water is present on it. Specifically, we use a linear combination of a small number of basis vector to approximate the spectral reflectance and estimate the original near-infrared reflectance from the visible reflectance (which does not depend on the presence or absence of water) to detect water. We conducted a number of experiments using real images and show that our method, which estimates near-infrared spectral reflectance based on the visible spectral reflectance, has better performance than existing techniques.

When considering the deployment of a radio communications network, the study of multipath interference and its impact on the quality of signal reception is of the outmost importance in order to meet the necessary performance requirements. This work considers specifically the case of the lunar surface as the mission scenario for a community of autonomous mobile exploration robots, which communicate through a radiofrequency network to accomplish their mission. In this application, the low height of the mobile robots makes the influence of multipath interference effects on the performance of the radio communication channel relevant. However, no specific information about lunar soil reflection coefficients characteristics is available for radiofrequency communication bands. This work reviews the literature on the electrical parameter of Lunar soil. From this base, the reflection coefficients are estimated for the assumed radio profile in different communications frequency bands. Finally, the results obtained are discussed.

The purpose of our research is to reproduce the appearance of frangible historical ink paintings for preserving frangible historical documents and illustrations. We, then, propose a method to reproduce both reflectance and transmittance of ink paintings simultaneously by stacking multiple sheets of printed paper. First, we acquire the relationship between printed ink patterns and the optical properties. Then, stacking printed multiple papers with acquired ink pattern according to the measurement, we realize to fabricate a photo-realistic duplication.

The Retinex theory assumes that large intensity changes correspond to reflectance edges, while smoothly-varying regions are due to shading. Some algorithms based on the theory adopt simple thresholding schemes and achieve adequate results for reflectance estimation. In this paper, we present a practical reflectance estimation technique for hyperspectral images. Our method is realized simply by thresholding singular values of a matrix calculated from scaled pixel values. In the method, we estimate the reflectance image by measuring spectral similarity between two adjacent pixels. We demonstrate that our thresholding scheme effectively estimates the reflectance and outperforms the Retinex-based thresholding. In particular, our methods can precisely distinguish edges caused by reflectance change and shadows.

The effective permittivity of the two-dimensional multilayered periodic structures which consist of the rectangular dielectric cylinders is examined numerically. The original periodic structure is replaced with a simple structure such as the dielectric slab. By using the reflectance of the periodic structure obtained by the FDTD method, the effective permittivity of the dielectric slab, which has the same reflectance as that of the periodic structure, is obtained by using the transcendental equation. In order to reduce the procedure to obtain the reflectance from the multilayered periodic structures, the reflectance from one-layered structure is used. The range of the application and validity of this procedure is examined.

We have investigated on a random-texturing process for multi-crystalline Si solar cells by plasmaless dry etching, with chlorine trifluoride (ClF3) gas treatments. The reflectance of textured surfaces was reduced to below 20% at a wavelength of 600 nm. In this study, we tried to improve the electrical characteristics by modifying the fabrication process. The substrate surfaces were dry etched by chlorine trifluoride gas and subsequently etched with an acid solution to form appropriate textured structures. The improved electrical characteristics were demonstrated.

Poor illumination and viewing conditions have negativeinfluences on the quality of an image, especially the contrast of the dark and bright region. Thus, captured and displayed images usually need contrast enhancement. Histogram-based or gamma correction-based methods are generally utilized for this. However, these methods are global contrast enhancement method, and since the sensitivity of the human eye changes locally according to the position of the object and the illumination in the scene, the global contrast enhancement methods have a limit. The spatial adaptive method is needed to overcome these limitations and it has led to the development of an integrated surround retinex (ISR), and estimation of dominant chromaticity (EDC) methods. However, these methods are based on Gray-World Assumption, and they use a general image formation model, so the color constancy is known to get poor results, shown through graying-out, halo-artifacts (ringing effects), and the dominated color. This paper presents a contrast enhancement method using a modified image formation model in which the image is divided into three components: global illumination, local illumination and reflectance. After applying the power constant value to control the contrast in the resulting image, the output image is obtained from their product to avoid or minimize a color distortion, based on the sRGB color representation. The experimental results show that the proposed method yields better performances than conventional methods.

We present a new method that can represent the reflectance of metallic paints accurately using a two-layer reflectance model with sampled microfacet distribution functions. We model the structure of metallic paints simplified by two layers: a binder surface that follows a microfacet distribution and a sub-layer that also follows a facet distribution. In the sub-layer, the diffuse and the specular reflectance represent color pigments and metallic flakes respectively. We use an iterative method based on the principle of Gauss-Seidel relaxation that stably fits the measured data to our highly non-linear model. We optimize the model by handling the microfacet distribution terms as a piecewise linear non-parametric form in order to increase its degree of freedom. The proposed model is validated by applying it to various metallic paints. The results show that our model has better fitting performance compared to the models used in other studies. Our model provides better accuracy due to the non-parametric terms employed in the model, and also gives efficiency in analyzing the characteristics of metallic paints by the analytical form embedded in the model. The non-parametric terms for the microfacet distribution in our model require densely measured data but not for the entire BRDF(bidirectional reflectance distribution function) domain, so that our method can reduce the burden of data acquisition during measurement. Especially, it becomes efficient for a system that uses a curved-sample based measurement system which allows us to obtain dense data in microfacet domain by a single measurement.

We propose an analysis method for Franz-Keldysh (FK) oscillations appearing in photoreflectance (PR) spectra of heterojunction device structures, which enables precise and simultaneous evaluation of the built-in electric field strength and band-gap energy. Samples for PR measurements were n+-GaAs/n-Al0.3 Ga0.7 As/i-GaAs heterostructures with different Al0.3Ga0.7As-layer thickness. We have found that the phase of the FK oscillations originating from the i-GaAs buffer layer depends on the Al0.3 Ga0.7 As-layer thickness. We have derived a calculation model for FK oscillations that includes the interference of probe light. From the comparison of the calculated spectra with the measured spectra, we conclude that mixing of the real and imaginary parts of a modulated dielectric function, which is caused by the probe-light interference, gives rise to the phase shift of the FK oscillations. Our FK-oscillation analysis method reduces ambiguity in the estimation of band-gap energy that is considerable in a conventional analysis.

A new approach is presented for recovering the 3-D shape from shading image. Photometric Stereo Method (PSM) is generally based on the direct illumination. PSM in this paper is modified with the indirect diffuse illumination method (IDIM), and then applied to hybrid reflectance model which consists of two components; the Lambertian reflectance and the specular reflectance. Under the hybrid reflectance model and the indirect diffuse illumination circumstances, the 3-D shape of objects can be recovered from the surface normal vector extracted from the surface roughness, the surface reflectance ratio, and the intensity value of a pixel. This method is rapid because of using the reference table, simplifies the restriction condition about the reflectance function in prior studies without any loss in performance, and can be applied to various types of surfaces by defining general reflectance function.

Physical and optical parameters within the atmosphere-ocean system have been retrieved by a multiple scattering analysis of the reflectance and degree of linear polarization data measured by the airborne POLDER sensor in Medimar campaign in 1991. Assuming an atmosphere-ocean system with a Cox-Munk type rough sea surface model, the theoretical reflectance and -degree of linear polarization were computed by the doubling and adding method for several different models. In this study the retrieval was made by assuming a fixed refractive index of the aerosol particles, i.e., Nr=1.33-0.0i. We obtained several important results in this study as follows: 1) By comparing computed results with the observed data at 0.85m, we rejected the oceanic type aerosol model and found Junge type aerosol model with its index range of 4.0v4.5 as an appropriate model for aerosols at the observation time. 2) The reflectance data analysis in the perpendicular plane rejected an isotropic Cox-Munk model, but it indicated that an anisotropic Cox-Munk model should be used in the sea surface wind field retrieval. 3) The surface wind speed was estimated to be 10.0m/secV15.0m/sec with an best estimate of V=12.5m/sec, which agrees with the observed wind speed of V=14.4m/sec. The range of the water column reflectance was also estimated to be 0.025rwc0.045 from Medimar reflectance data at 0.45m. 4) Further study should be made for other refractive indices of the aerosol particles. More refinement of the present multiple scattering code to include upwelling polarization components from below the sea surface is also necessary.

The Bidirectional Reflectance Distribution Function (BRDF) is an intrinsic measurement of directional properties of the earth's surface. However, the estimation of the BRDF requires many remote sensing measurements of a given surface target from different viewing angles. In addition, a good atmospheric correction scheme is a prerequisite for such an attempt. The airborne POLDER sensor measures successively reflected radiation by terrestrial surfaces in a framed image form at different viewing angles during a single airplane pass, like taking snap-shot pictures. A specially improved atmospheric correction algorithm which is applicable to a framed image data by POLDER sensor is presented. The observed reflectance images taken successively by the airborne POLDER at slightly different viewing angles are converted to a series of surface albedo images by applying our atmospheric correction algorithm. Then, the BRDFs for three surface covers, namely, "River Water," "Forest," and "Rice Field," are estimated by using successive albedo images. It is found that the BRDF for "River Water" follows Lambert law at both 550nm and 850nm. It is also found that the BRDFs for "Forest" and "Rice Field" follow Lambert's law at 550nm, but they follow an anisotropic reflection law at 850nm and fitting parameters for their BRDFs are presented.

In this paper, we extend two-image photometric stereo method to treat a concave polyhedron, and present an iterative algorithm to remove the influence of interreflections. By the method we can obtain the shape and reflectance of a concave polyhedron with perfectly diffuse (Lambertian) and unknown constant reflectance. Both simulation and experiment show the feasibility and accuracy of the method.

This paper describes a new method to determine the 3-D position coordinates of a Lambertian surface from four shaded images acquired with an actively controlled, nearby moving point light source. The method treats both the case when the initial position of the light source is known and the case when it is unknown.

This paper proposes a new method to determine the shape of a surface by learning the mapping between three image irradiances observed under illumination from three lighting directions and the corresponding surface gradient. The method uses Phong reflectance function to describe specular reflectance. Lambertian reflectance is included as a special case. A neural network is constructed to estimate the values of reflectance parameters and the object surface gradient distribution under the assumption that the values of reflectance parameters are not known in advance. The method reconstructs the surface gradient distribution after determining the values of reflectance parameters of a test object using two step neural network which consists of one to extract two gradient parameters from three image irradiances and its inverse one. The effectiveness of this proposed neural network is confirmed by computer simulations and by experiment with a real object.