Spectral Reflectance Reconstruction with Nonlinear Composite Model of the Metameric Black.

Metamerism phenomenon is an important problem in spectral reflectance reconstruction and color reproduction. In this paper, a 3-primary color CCD camera is used to acquire spectral information in CIE standard illuminant D65 and a nonlinear composite model is established, including principal component analysis and neural network method (PCA-NET) to modify the Matrix R Method based on the Metameric Black theory. The standard Munsell color card is used in spectral reflectance reconstruction experiment and the results are evaluated and discussed. The experimental results verified that the PCA-NET algorithm can accurately fit the nonlinear relationship between the output signal of the camera and the principal component coefficients; and it can be used in the R matrix algorithm instead of the linear algorithm; the new method can serve as a promising technique for building a spectral image database whihc is better than the original Matrix R Method. In the fixed illumination environment, the mean RMS of the test set is 0.76 improved, and the mean STD of the test set is 0.85 improved, which can effectively improve the accuracy of spectral reflectance reconstruction. The modified matrix R method has the advantages of higher accuracy and easy implementation, and it can be used in the field of color reproduction and spectral reflectance reconstruction.

Research on Ground-Based LWIR Hyperspectral Imaging Remote Gas Detection.

The new progress of ground-based long-wave infrared remote sensing is presented, which describes the windowing spatial and temporal modulation Fourier spectroscopy imaging in details. The prototype forms the interference fringes based on the corner-cube of spatial modulation of Michelson interferometer, using cooled long-wave infrared photovoltaic staring FPA (focal plane array) detector. The LWIR hyperspectral imaging is achieved by the process of collection, reorganization, correction, apodization, FFT etc. from data cube. Noise equivalent spectral radiance (NESR), which is the sensitivity index of CHIPED-1 LWIR hyperspectral imaging prototype, can reach 5.6 x 10⁻8 W · (cm⁻¹ · sr · cm²)⁻¹ at single sampling. The data is the same as commercial temporal modulation hyperspectral imaging spectrometer. It can prove the advantage of this technique. This technique still has space to be improved. For instance, spectral response range of CHIPED-1 LWIR hyperspectral imaging prototype can reach 11. 5 µm by testing the transmission curve of polypropylene film. In this article, choosing the results of outdoor high-rise and diethyl ether gas experiment as an example, the authors research on the detecting method of 2D distribution chemical gas VOC by infrared hyperspectral imaging. There is no observed diethyl ether gas from the infrared spectral slice of the same wave number in complicated background and low concentration. By doing the difference spectrum, the authors can see the space distribution of diethyl ether gas clearly. Hyperspectral imaging is used in the field of organic gas VOC infrared detection. Relative to wide band infrared imaging, it has some advantages. Such as, it has high sensitivity, the strong anti-interference ability, identify the variety, and so on.

[A novel spatial modulation Fourier transform spectrometer with adjustable spectral resolution].

In the premise of fulfilling the application requirement, the adjustment of spectral resolution can improve efficiency of data acquisition, data processing and data saving. So, by adjusting the spectral resolution, the performance of spectrometer can be improved, and its application range can be extended. To avoid the problems of the fixed spectral resolution of classical Fourier transform spectrometer, a novel type of spatial modulation Fourier transform spectrometer with adjustable spectral resolution is proposed in this paper. The principle of the novel spectrometer and its interferometer is described. The general expressions of the optical path difference and the lateral shear are induced by a ray tracing procedure. The equivalent model of the novel interferometer is analyzed. Meanwhile, the principle of the adjustment of spectral resolution is analyzed. The result shows that the novel spectrometer has the merits of adjustable spectral resolution, high stability, easy assemblage and adjustment etc. This theoretical study will provide the theoretical basis for the design of the spectrometer with adjustable spectral resolution and expand the application range of Fourier transform spectrometer.

[Correlation of visual spectral response with aging and its effect on color discrimination].

The variation in normal observers' color perception and discrimination will occur with the aging effect. The authors carried out a psychophysical experiment with the method of binocular observational technique. Three observers at the age of 21, 32 and 58 were organized to match the 9 printed color samples on EIZO monitor with the repetition of 7 times. Groups of data for cross-media color matching with different age were established to investigate the response of photoreceptor cells. The results indicated that with the aging effect the chroma of the matched color will decrease obviously and the spectral response of the blue channel will decrease for blue and purple colors. The results validate the prediction of CIEPO06 model to some extent and provide some theoretical basis and experimental supports for the application of color reproduction and the color evaluation of the products related to age.

[Spectrum analysis and measurment research on visual density of the national standard densitometer].

Visual density is an important index for the estimation of photographic film and visual photo. The development of biomedical image and macromolecule image needs high measurement uncertainty of visual density in spectrum characteristic. The ISO standard of visual density measurement conditions was modified in 2001. A series of equipments designed for densitometer enhance the spectral matching between the national standard densitometer and the ISO standard function. And a new measurement formula is given based on theory analysis. According to the measurement data and uncertainty analysis, the combined uncertainties are 0.001 1 (0 < D < 4.0) and 0.003 1 (4.0 < or = D < 6.0).

[High precision all-reflection Fourier transform imaging spectrometer spectral calibration using homogeneous broadening of the wave number model].

All-reflection Fourier transform imaging spectrometer (ARFTIS) is a novel imaging spectrometer. The specialty is not only high spectrum resolution, but also wide band and non-chromatism. It is good for remote sensing field of wide band imaging. Single spectrum calibration, average calibration and weighted average calibration are three common calibration methods. However, they all are limited. Because they cannot meet the demand on both convenience and high precision. In the present paper, the authors propose a novel model for spectrum calibration. It can work in high precision with single spectrum calibration. At the same time, the method is steady, and the average error is less than 5% with multi-bands calibration. It provides a convenient way for the non-professional calibration situation and outer simply calibration work.

[Spectral reconstruction using algebraic reconstruction technology for Fourier transform computed tomography imaging spectrometer].

In the present paper, the authors will introduce our research on spectral reconstruction of Fourier transform computed tomography imaging spectrometer by means of the algebraic reconstruction technology. A simulation experiment was carried out to demonstrate the algorithm. The spatial similarities and spectral similarities were evaluated using the normalized correlation coefficient. The performance of ART was evaluated when the quantity of projection is 45. In that case, filter back projection can't work well. Actual spectral slices were reconstructed by using ART in the last part of this paper.

[Fabrication and analysis of red-green resonant complementary optically variable sub-wavelength microstructures].

Principles of design and production of dual-layer sub-wavelength grating microstructures are analyzed thoroughly. Novel methods for designing and fabricating such structures, with the characteristics of using rectangular grating index profiles when designed and using holographic interference lithography and coating processes when produced, are proposed. Microstructures fabricated by use of this method, will have the same resonant and optically variable properties with pre-designed structures, even improving its color qualities of lights reflected. A sub-wavelength security microstructure with the unique performances of red-green resonant complementary optically variability in color was designed and manufactured successfully and its resonant optically variable spectrum and color changing characteristics were verified theoretically and experimentally. Study results indicate that sinusoidal grating microstructures manufactured have the same resonant and optically variable characteristics, such as the resonant spectrum, color, spectral peak and peak splits, etc. with the pre-designed structures. A rectangular index profile grating is not the necessary requirement to produce resonance behaviors and the grating regions can have any profile such as the holographic type as long as its diffraction characteristics and equivalent waveguide representation are the same with the designed rectangular grating microstructures. The methods proposed are feasible in practice, lowering the making complexity and with potential of low-cost mass production commercially by use of the current holographic manufacture equipments.

[Identification of cucumber disease using hyperspectral imaging and discriminate analysis].

Hyperspectral imaging (400-720 nm) and discriminate analysis were investigated for the detection of normal and diseased cucumber leaf samples with powdery mildew (Sphaerotheca fuliginea), angular leaf spot (Pseudomopnas syringae), downy mildew (Pseudoperonospora cubensis), and brown spot (Corynespora cassiicola). A hyperspectral imaging system was es tablished to acquire and pre-process leaf images, as well as to extract leaf spectral properties. Owing to the complexity of the original spectral data, stepwise discriminate and canonical discriminate were executed to reduce the numerous spectral information, in order to decrease the amount of calculation and improve the accuracy. By the stepwise discriminate we selected 12 optimal wavelengths from the original 55 wavelengths, and after the canonical discriminate, the 55 wavelengths were reduced to 2 canonical variables. Then the discriminate models were developed to classify the leaf samples. The result shows that the stepwise discriminate model achieved classification accuracies of 100% and 94% for the training and testing sets, respectively. For the canonical model, the classification accuracies for the training and testing sets were both 100%. These results indicated that it is feasible to identify and classify cucumber diseases using hyperspectral imaging technology and discriminate analysis. The preliminary study, which was done in a closed room with restrictions to avoid interference of the field environment, showed that there is a potential to establish an online field application in cucumber disease detection based on visible spectroscopy.

[Horticultural plant diseases multispectral classification using combined classified methods].

The research on multispectral data disposal is getting more and more attention with the development of multispectral technique, capturing data ability and application of multispectral technique in agriculture practice. In the present paper, a cultivated plant cucumber' familiar disease (Trichothecium roseum, Sphaerotheca fuliginea, Cladosporium cucumerinum, Corynespora cassiicola, Pseudoperonospora cubensis) is the research objects. The cucumber leaves multispectral images of 14 visible light channels, near infrared channel and panchromatic channel were captured using narrow-band multispectral imaging system under standard observation and illumination environment, and 210 multispectral data samples which are the 16 bands spectral reflectance of different cucumber disease were obtained. The 210 samples were classified by distance, relativity and BP neural network to discuss effective combination of classified methods for making a diagnosis. The result shows that the classified effective combination of distance and BP neural network classified methods has superior performance than each method, and the advantage of each method is fully used. And the flow of recognizing horticultural plant diseases using combined classified methods is presented.

[Reproduction features of reflectance spectrum of natural plant flower color].

Based on the sRGB color space as an important color space of computer display, the authors explored color reproduction features in sRGB. In the terms of "color clipping" of color space transformation from CIE1931XYZ to sRGB, the color reproduction errors in sRGB of 218 reflectance spectra of natural plant flower color were examined. Considering the importance of D65 illumination, the reproduction features of natural color under D65 were emphasized. It was concluded as follows. Firstly, "color clipping" is the key cause of color transformation error of the natural plant color when it is transformed from CIE1931XYZ to sRGB color space. Secondly, under D65 eight orange and yellow reflectance spectra in 218 natural color show clipping in sRGB color space, accounting for 3.7% of all samples. Finally, the color reproduction of natural plant flower color in sRGB under D65 is the best, while the A illumination is the worst.

[Study of approaches to spectral reflectance reconstruction based on digital camera].

It is still challenging to reconstruct the spectral reflectance of a surface using digital cameras under given luminance and observation conditions. A new approach to solving the problem which is based on neural network and basis vectors is proposed. At first, the spectral reflectance of the sample surface is measured by spectrometer and the response of an digital camera is recorded. Then the reflectance is represented as a linear combination of several basis vectors by singular value decomposition (SVD). After that, a neural network is trained so that it is able to approximate the relationship between the camera responses and the coefficients of basis vectors accurately. In the end, the spectral reflectance can be reconstructed based on the neural network and basis vectors. In the present paper, the authors reconstructed the spectrum reflectance based on neural network and basis vectors. Compared with other traditional methods, neural network expands the space of unknown function F(S) from linear functions to more general nonlinear functions, which gives more accurate estimation of the coefficients alphak and better reflectance reconstruction. Results show that the reflectance of standard Munsell color patch (Matte) can be reconstructed successfully with mean of RMS which is 0.0234. Compared with linear approximation method, reconstruction of standard Munsell color patch (Matte) using this approach reduces the reconstruction error by 67%. Since the neural network can be implemented by Matlab neural network toolbox, this method can be easily adopted in many other cases. Therefore we conclude that this approach has advantages of higher accuracy, easy implementation and adaptation, thus can be used in many applications.

[Multispectral imaging system for the plant diseases and insect pests diagnosis].

For a reliable diagnosis of plant diseases and insect pests, it is very important to reproduce the original color of the object. But it is not certain by conventional color imaging systems. Multispectral imaging techniques are capable of providing additional useful spectral information of common pathological samples using image acquisition The authors present a multispectral imaging system for the diagnosis. This system uses 16 narrow-band filters, a monochrome CCD camera, and standard illumination environment. Spectral match angle and color difference can be obtained through measurements and analysis of 8 Macbeth color patch using PR-715 spectraScan and multispectral imaging system. In addition, the color image and spectral reflectance of cucumber diseased leaves were reproduced using the multispectral imaging system. In the experiment, it was confirmed that the system realized good accuracy in the color reproduction and spectral reflectance reproduction from a limited number of color bands.

[Cucumber diseases diagnosis using multispectral imaging technique].

For a reliable diagnosis of plant diseases and insect pests, spectroscopy analysis technique and mutispectral imaging technique are proposed to diagnose five cucumber diseases, namely Trichothecium roseum, Sphaerotheca fuliginea, Cladosporium cucumerinum, Corynespora cassiicola and Pseudoperonospora cubensis. In the experiment, the cucumbers' multispectral images of 14 visible lights channels, near infrared channel and panchromatic channel were captured using narrow-band multispectral imaging system under standard observation environment. And the 5 cucumber diseases, healthy leaves and reference white were classified using their multispectral information, the distance, angle and relativity. The discrimination of Trichothecium roseum, Sphaerotheca fuliginea, Cladosporium cucumerinum, and reference white was 100%, and that of Pseudoperonospora cubensis and healthy leaves was 80% and 93.33% respectively. The mean correct discrimination of diseases was 81.90% when the distance and relativity were used together. The result shows that the method realized good accuracy in the cucumber diseases diagnosis.