Top PDF Hyperspectral Imaging System Model Implementation and Analysis

Hyperspectral Imaging System Model Implementation and Analysis

Hyperspectral Imaging System Model Implementation and Analysis

expandability of the system. This program needs the configuration file to initialize the target, back- ground, scene and sensor objects according to the specified parameters and files. Then the input mean and covariance library will be interpolated accord- ing to the wavelengths of the chosen sensor. Also the mean parameters will be used to generate tape5 files for different MODTRAN runs. The process of generating tape5 should strictly obey the tape5 file format specified in the MODTRAN manual, or a single space could result in unexpected results. Af- ter each MODTRAN run, the output tape7 file will be parsed and read from different columns into different vectors. Since MODTRAN has a different unit and usually a higher resolution than the sensor, the tape7 unit results in units of wavenumber need to be converted back to wavelength. Also according to the sensor wavelength and bandwidth, channel response functions will be ap- plied on the output data to generate Gaussian shape centered on the sensor wavelengths. For other calculations as discussed in Chapter 3, the implementa- tion is straight forward. At last, the predicted radiance and SNR for different classes are obtained, and the ROC curve is calculated and saved.
Show more

116 Read more

Implementation of webcam-based hyperspectral imaging system

Implementation of webcam-based hyperspectral imaging system

The results showed that the developed system could successfully reconstruct the spectral images in different wavelength in visible and near-infrared regions with good spectral and spatial resolutions. The spectral resolution of this system was about 2nm and its spatial resolution was about 1 mm for a 10 cm long object. Having less spatial resolution in the reconstructed images of the plasma jet in the emission mode is due to fluctuating of the plasma flame. On the other hand, due to the stability of the samples, in both transmission and reflection modes, the spectral resolution was better. In order to capture spectral images with a high spatial resolution from fractionating sources, faster methods like staring or snapshot could be used.
Show more

9 Read more

Fast implementation of singular spectrum analysis for effective feature extraction in hyperspectral imaging

Fast implementation of singular spectrum analysis for effective feature extraction in hyperspectral imaging

To highlight the difference between SSA and F-SSA, their workflows are illustrated in Fig. 2 for comparison. As can be seen, in F-SSA only the embedding, transformation and diagonal averaging procedures are required for all Q pixels, yet the transformation matrix derived from the representative pixel is commonly used to all of them. This can highly reduce the complexity of SSA when applied in HSI, as only an initial SVD analysis is demanded, which is carried out on a representative pixel, i.e. either the mean or the median spectral profile of the hypercube. The efficiency and efficacy of F-SSA are compared with SSA as detailed in the next section.
Show more

9 Read more

Fast implementation of two-dimensional singular spectrum analysis for effective data classification in hyperspectral imaging

Fast implementation of two-dimensional singular spectrum analysis for effective data classification in hyperspectral imaging

Fig.11. Running time (s) per stage and different L 2D in conventional 2D-SSA for 92AV3C (left), Pavia UA (middle) and Salinas C (right). Finally, a global comparison of the SSA methodologies, with classification accuracy and running time, is provided in Table XVI. The better performance of the 2-D methodologies in classification accuracy is clear, however, the pixel-based implementation from the 1-D cases involves a faster running time, basically because trajectory matrices in 1-D are smaller. Discussions can be derived from this fact, regarding what a good trade-off between accuracy and complexity can be when working with HSI. From our point of view, the classification accuracy comes first; looking for accuracies close to 100%, and that is probably the reason why most efforts in HSI are focused on the highest-accuracy problem. Nevertheless, complexity is a factor to bear in mind, making some implementations unfeasible. A good example is 2D-EMD in Salinas C, where it requires 1056 s, something incompatible with fast tasks. This issue points out our fast implementation importance and contribution.
Show more

21 Read more

Fast implementation of two-dimensional singular spectrum analysis for effective data classification in hyperspectral imaging

Fast implementation of two-dimensional singular spectrum analysis for effective data classification in hyperspectral imaging

Fig.11. Running time (s) per stage and different L 2D in conventional 2D-SSA for 92AV3C (left), Pavia UA (middle) and Salinas C (right). Finally, a global comparison of the SSA methodologies, with classification accuracy and running time, is provided in Table XVI. The better performance of the 2-D methodologies in classification accuracy is clear, however, the pixel-based implementation from the 1-D cases involves a faster running time, basically because trajectory matrices in 1-D are smaller. Discussions can be derived from this fact, regarding what a good trade-off between accuracy and complexity can be when working with HSI. From our point of view, the classification accuracy comes first; looking for accuracies close to 100%, and that is probably the reason why most efforts in HSI are focused on the highest-accuracy problem. Nevertheless, complexity is a factor to bear in mind, making some implementations unfeasible. A good example is 2D-EMD in Salinas C, where it requires 1056 s, something incompatible with fast tasks. This issue points out our fast implementation importance and contribution.
Show more

20 Read more

Hyperspectral system for Imaging of skin chromophores and blood oxygenation

Hyperspectral system for Imaging of skin chromophores and blood oxygenation

1. Introduction Methods of in vivo skin chromophore assessment and blood oxygen measurements have a long history. 1 Conventional techniques utilize measurements at several wavelengths in the visible and NIR ranges (usually 2-4 wavelengths) or color sensors rather than real spectral measurements. 2,3 However, to our knowledge, no portable, compact, lightweight, hand-held and robust hyperspectral devices capable of skin chromophore content analysis (2D mapping), skin perfusion and monitoring of blood oxygenation at the same time have been presented up to date.

5 Read more

Hyperspectral imaging system for in-vivo quantification of skin pigments

Hyperspectral imaging system for in-vivo quantification of skin pigments

The SpectraCam® device presented here allows good characterization of the human skin. A far as we known, it is the first available device capturing in-vivo images of the skin over the whole visible spectrum under fluorescent or white light. The use of cross- polarization enables removing light reflections of the stratum corneum, which may be an important error factor in chromophores quantification. The model that we use to extract the skin parameters from the multispectral images is the Kubelka-Munk model with Saunderson correction. While the Saunderson correction seems to be ignored in most existing works, its use guarantees better accuracy. The model allows retrieving six parameters of Caucasian skin: epidermis depth, melanin volume fraction, blood volume fraction, oxygen saturation and bilirubin volume fraction. The measurement of this latter parameter is also an originality of our work compared to the existing works. Maps of each of these parameters can be displayed to observe different structures such as blood vessels, pores, hematoma or pigmented spots. A spectral deviation map is also displayed to highlight structures that do not fit well with the developed skin model.
Show more

11 Read more

Hyperspectral Imaging for Non-Contact Analysis of Forensic Traces

Hyperspectral Imaging for Non-Contact Analysis of Forensic Traces

The implementation of digital micro-mirror devices (DMDs) is another recent development in HSI [10]. In this setup, only the region of interest is illuminated. Such systems reduce variations in the spectra arising from scattered light from the background and nearby objects. Finally, the image acquisition system can be optimized for the application. The desire for on- line monitoring within the process industries has seen the emergence of real-time online systems typically employing line-scanning approaches. This line scanning setup also offers potential for large- scale forensic science applications, where instead of using a moving stage or conveyor to pass a specimen or product past the detector, the detector itself is moved over a large stationary area of interest such as a wall, a floor or an entire scene of investigation (see Figure 5).
Show more

40 Read more

Characterization of Chromobacterium violaceum pigment through a hyperspectral imaging system

Characterization of Chromobacterium violaceum pigment through a hyperspectral imaging system

Spectral reflectance recovery In order to retrieve the spectral reflectance of biological samples, several stages have to be performed. First, the sequence starts with the scene scanning due to the nature of the of the PBHC acquisition process. Second, the input radiance of a spatial line is decomposed and sampled into P spatial pixels and Q spectral bands, taking S line sam- ples at different times. Hence, the entire target scene is mapped into a hypercube of dimensions P × Q × S. Third, the hyperspectral data must be calibrated to compensate for any degrading effect produced during the signal trans- duction. To do so, we have mathematically represented the hyperspectral response by the following first-order model:
Show more

9 Read more

Single-Kernel Maize Analysis by Near-Infrared Hyperspectral Imaging

Single-Kernel Maize Analysis by Near-Infrared Hyperspectral Imaging

C ALIBRATION D EVELOPMENT Two multivariate regression algorithms were compared for the full-spectrum calibration tests: partial least squares (PLS) regression (Wold et al., 1984; Geladi and Kowalski, 1986; Martens and Næs, 1989) and principal component regression (PCR) (Næs and Martens, 1988; Martens and Næs, 1989). While both techniques are latent-variable regression techniques, it was anticipated that one or the other may have an advantage. Because PLS seeks to maximize the covarian- ce between the predictor and predicted variables, poor quality reference data may lead to the derivation of factors correlated with erroneous reference data. On the other hand, since the factors derived by PLS are ordered according to decreasing covariance between predictor and predicted variables, using a PLS model should result in fewer latent variables being retained, hopefully increasing the signal-to- noise ratio of the model. Prior to deriving each regression, the spectra were mean-centered, and the reference data was mean -centered and scaled to unit variance to improve the condition of matrices for inversion.
Show more

12 Read more

Near infrared hyperspectral imaging for forensic analysis of document forgery

Near infrared hyperspectral imaging for forensic analysis of document forgery

Among all the pre-processing techniques used to treat the data set, SNV showed the best results. After preprocessing, a PCA model was built and the first 10 PCs were obtained. Figure 6 shows the score images related to two PCs of three different samples, used as an example. As commented in Section 2, sample S1 was produced by adding two zeros to the number 20 to form 2000. In sample S23, the number 10 was transformed in 4000 by modifying the number 1 into a 4 and adding two zeros. In sample S20, the number 10 was also modified and transformed into 7000, as shown in Figures 2d, 2e and 2f.
Show more

9 Read more

Singular spectrum analysis for effective feature extraction in hyperspectral imaging

Singular spectrum analysis for effective feature extraction in hyperspectral imaging

k  and K  N  L  1 . It is worth noting that the matrix X has equal values along the anti-diagonals, thus it is actually a Hankel matrix by definition. In fact, based on a property of the matrix X [12], the SSA algorithm can be implemented symmetrically in two intervals, i.e. L [ 1 , round ( N / 2 )] and L  [ ceil (( N  1 ) / 2 ), N ] . For a given L , the equivalent implementation can be found for another L '  K , leading to the same results. In addition, just remark that both singular ends from the global interval, 1 and N , do not provide a SSA implementation.
Show more

5 Read more

Hyperspectral imaging for food applications

Hyperspectral imaging for food applications

Index Terms— Signal Processing, Image Processing, Classifiers, Spectral Imaging 1. INTRODUCTION Where conventional digital imaging devices capture light over one (greyscale) or three (red, green, blue) distinct portions of the electromagnetic spectrum, a hyperspectral imaging (HSI) system acquires light at hundreds or even thousands of differ- ent spectral bands. Similar to the way in which a spectrometer produces a spectrum of the light captured at a single point, an HSI system produces a spectrum for each pixel in the image. This combination of spatial and spectral detail provides sig- nificantly more information about a scene. Historically, appli- cations of HSI have tended to be large and complex, such as remote sensing, wide area surveillance and aircraft-based sys- tems [1, 2]. Due to the price and size of HSI systems, it was only in these areas that the technology was a viable tool. The recent reduction in both price and size, however, has made hy- perspectral imaging a more attractive option for lab based ap- plications such as forensic science [3] and, in particular, food quality analysis [4]. In this paper, several analysis techniques are explained before the results of four different implemen- tations of HSI in food based applications are explained. The
Show more

6 Read more

Evaluation of illumination system uniformity for wide-field biomedical hyperspectral imaging

Evaluation of illumination system uniformity for wide-field biomedical hyperspectral imaging

While these results are encouraging, we identi fied a number of challenges for future investigation. For spectral uniformity, we used a relatively wide bandpass of 100 nm. In applications such as fluorescence imaging, where potential non-uniformities may occur on narrower ranges, such as 10 nm or less, simulating illumination on this scale will be necessary but computationally expensive. All three systems performed relatively poorly in the angular domain compared to the respective spatial distributions. This result suggests that designing new approaches that improve on this aspect of illumination uniformity would be of value for implementation of future HSI systems. For low light level applications such as fluorescence imaging, current illumination systems may not be suf ficient to maximise detection capabilities. The model- ling approach demonstrated here could in future be used to rapidly evaluate novel illumination designs that improve upon angular uniformity or maximise performance by multiplexing broadband and narrowband illumination.
Show more

11 Read more

A clinically translatable hyperspectral endoscopy (HySE) system for imaging the gastrointestinal tract.

A clinically translatable hyperspectral endoscopy (HySE) system for imaging the gastrointestinal tract.

the system satisfies the optical requirements for the real-time clinical HySE. We also demonstrated the potential for quantita- tive data extraction from biomedical samples. We first showed that unsupervised multivariate analysis can differentiate tissue regions in chicken tissue according to their spectral profile. We then established the capability of the system to measure oxyge- nation saturation levels in blood in controlled tissue mimicking phantoms, and derived absorption spectra from a variety of ex vivo tissue types in biopsies taken from the human oesophagus and stomach, showing clear differences between the spectra of oesophageal cancer and other tissue types. Finally, we demon- strated the potential of HySE in realistic endoscopic imaging scenario within an intact ex vivo pig oesophagus, obtaining relative concentrations of an applied stain using linear spectral unmixing.
Show more

13 Read more

Precautionary analysis of sprouting potato eyes using hyperspectral imaging technology

Precautionary analysis of sprouting potato eyes using hyperspectral imaging technology

Wavelength/nm 709.72 712.26 719.88 730.06 733.88 737.7 740.25 747.9 749.17 3.3 Classification of sprouting potato eyes In this study, fitting parameters calculated by SFA, along with the combination with selected wavelengths by SPA were introduced as the indicators into FDA. The recognition results were shown in Table 3. Regularization parameter and RBF kernel parameter are two important parameters determined by two-dimensional nonlinear unconstrained optimization method and interaction validation of training. L-fold was set as 10 in tunelssvm function in establishing LSSVM model. The prediction results were shown in Figure 7.
Show more

5 Read more

Texture Quality Analysis of Rainbow Trout Using Hyperspectral Imaging Method

Texture Quality Analysis of Rainbow Trout Using Hyperspectral Imaging Method

agriculture include vegetation mapping, crop disease, stress and yield detection, component identification in plants, and detection of impurities. There is growing interest in HSI for safety and quality assessments of agro-food products (15). Wu et al. applied Partial Least Square Regression (PLSR) to establish a quantitative model between hyperspectral images of salmon fillets and their corresponding parameters of hardness, cohesiveness, and adhesiveness (9). The Correlation Coefficients (r) of 0.665, 0.555 and 0.606 while the Root Mean Square Errors of Cross Validation (RMSECV) of 4.09, 0.067 and 0.504 were achieved for hardness, cohesiveness, and adhesiveness, respectively. The results demonstrated that hyperspectral imaging technique has the potential to quantitatively measure texture of salmon fillet in a rapid and non-invasive way. It was concluded that R 2 for classification is better than regression when the target is the texture analysis of meat product. Liu et al. attempted to classify beef samples into tender and tough classes using spectroscopy which resulted in a model with correct classification of 83% (16). Soft Independent Modeling of Class Analogy of principal component analysis (SIMCA/PCA) model of measured tenderness showed great promise in the classification of tender and tough meats with over 96% success. While the R 2 in regression model was between 0.49 and 0.55 for tenderness and sensory chewiness, respectively. C-1: Not clear?? The Hyperspectral imaging method has acceptable results in other fields such as detection and quantification of ergot bodies in cereals (17), external insect infestations on jujube fruit (18), monitoring quality of tomato fruit (19). The main aim of this research is to model texture of rainbow trout by linking a compression test (as time-consuming and destructive method) and hyperspectral imaging (as fast and nondestructive method) in duration of storage.
Show more

25 Read more

GaiaField-Pro Hyperspectral Imaging Camera

GaiaField-Pro Hyperspectral Imaging Camera

C o m b i n e d w i t h b l o o d c e l l s m o r p h o l o g i c a l characteristics and the existing method of blood cell analysis, researchers research the data of the normal blood / leukemia blood of hyperspectral imaging.The characteristics of red blood cells, lymphocytes,leukemia cells were analyzed by microscopic hyperspectral imaging, and the implementation of the diseased cells segmentation and morphological parameter quantitative calculation.

5 Read more

Final Segmenting Schistosomiasis on Hyperspectral imaging

Final Segmenting Schistosomiasis on Hyperspectral imaging

Schistosomiasis is considered one of the Neglected Tropical Diseases. The combined concept will be based on a region-based distributing function with a novel edge detector which is derived from phase congruency and grayscale thinning by the threshold superposition. Image segmentation algorithm is designed in order to overcome the distinct challenges posed by schistosomes. Hyperspectral analysis of the parasite is made for the deeper analyzing of the bilharzia. The application of high-throughput screening method to the other parasitic disease. The highly conservative nature of grayscale morphological thinning by superposition is hosted collaboration system.
Show more

9 Read more

Custom scanning hyperspectral imaging system for biomedical applications: modeling, benchmarking, and specifications

Custom scanning hyperspectral imaging system for biomedical applications: modeling, benchmarking, and specifications

The design modalities of HSI systems are well documented [13], and the multiplicity of different spectroscopic configurations for material classification is certainly notable, with various design characteristics and tradeoffs (see [14–16]), and increasing in number in recent years (e.g., [17–22]). The main characteristics of the most ubiquitous imaging systems are left in Table 1. In scanning imaging systems in particular, the spectra of a single point or line in an object plane is measured at a time, and a complete spatial image is achieved by moving either the sample, the imaging device, or components that may change the direction of acquisition (a thorough description of these devices can be found in the literature [12,13]). To the authors’ knowledge, unfortunately, there are no reported reviews on scanning imaging system design, modeling, and benchmarking, so relevant tradeoffs may have been left unexplored. Prototyping a scanning imaging system is indeed a challenging job but, as will be described in the following sections, in practice there are a few caveats and considerations which, once thoroughly reviewed, greatly illustrate the most relevant difficulties of HSI imaging system design. Encouraging the exploitation and implementation of more custom-built devices for biomedical applications, as well as hopefully endowing some degree of standardization for future cases, may be deemed desireable.
Show more

22 Read more

Show all 10000 documents...