scholarly journals Interpretation of the Reflectance Spectra of Lithium (Li) Minerals and Pegmatites: A Case Study for Mineralogical and Lithological Identification in the Fregeneda-Almendra Area

2021 ◽  
Vol 13 (18) ◽  
pp. 3688
Author(s):  
Joana Cardoso-Fernandes ◽  
João Silva ◽  
Mônica M. Perrotta ◽  
Alexandre Lima ◽  
Ana C. Teodoro ◽  
...  
Keyword(s):  
Real Life ◽  
Spectroscopic Studies ◽  
Hyperspectral Data ◽  
Diagnostic Feature ◽  
Target Class ◽  
Spectral Behavior ◽  
Spectral Curves ◽  
Argillic Alteration ◽  
Complementary Techniques ◽  
Geochemical Studies

Reflectance spectroscopy has been used to identify several deposit types. However, applications concerning lithium (Li)-pegmatites are still scarce. Reflectance spectroscopic studies complemented by microscopic and geochemical studies were employed in the Fregeneda–Almendra (Spain–Portugal) pegmatite field to analyze the spectral behavior of Li-minerals and field lithologies. The spectral similarity of the target class (Li-pegmatites) with other elements was also evaluated. Lepidolite was discriminated from other white micas and the remaining Li-minerals. No diagnostic feature of petalite and spodumene was identified, since their spectral curves are dominated by clays. Their presence was corroborated (by complementary techniques) in petalite relics and completely replaced crystals, although the clay-related absorption depths decrease with Li content. This implies that clays can be used as pathfinders only in areas where argillic alteration is not prevalent. All sampled lithologies present similar water and/or hydroxide features. The overall mineral assemblage is very distinct, with lepidolite, cookeite, and orthoclase exclusively identified in Li-pegmatite (being these minerals crucial targets for Li-pegmatite discrimination in real-life applications), while chlorite and biotite can occur in the remaining lithologies. Satellite data can be used to discriminate Li-pegmatites due to distinct reflectance magnitude and mineral assemblages, higher absorptions depths, and distinct Al–OH wavelength position. The potential use of multi- and hyperspectral data was evaluated; the main limitations and advantages were discussed. These new insights on the spectral behavior of Li-minerals and pegmatites may aid in new Li-pegmatite discoveries around the world.

scholarly journals FPGA-Based On-Board Hyperspectral Imaging Compression: Benchmarking Performance and Energy Efficiency against GPU Implementations

2020 ◽  
Vol 12 (22) ◽  
pp. 3741 ◽  
Author(s):  
Julián Caba ◽  
María Díaz ◽  
Jesús Barba ◽  
Raúl Guerra ◽  
Jose A. de la Torre and Sebastián López
Keyword(s):  
Reconfigurable Computing ◽  
Power Efficiency ◽  
Real Life ◽  
Hyperspectral Data ◽  
Actual Behavior ◽  
Power Budget ◽  
Image Block ◽  
Power Efficient ◽  
Time Requirements ◽  
Computing Platforms

Remote-sensing platforms, such as Unmanned Aerial Vehicles, are characterized by limited power budget and low-bandwidth downlinks. Therefore, handling hyperspectral data in this context can jeopardize the operational time of the system. FPGAs have been traditionally regarded as the most power-efficient computing platforms. However, there is little experimental evidence to support this claim, which is especially critical since the actual behavior of the solutions based on reconfigurable technology is highly dependent on the type of application. In this work, a highly optimized implementation of an FPGA accelerator of the novel HyperLCA algorithm has been developed and thoughtfully analyzed in terms of performance and power efficiency. In this regard, a modification of the aforementioned lossy compression solution has also been proposed to be efficiently executed into FPGA devices using fixed-point arithmetic. Single and multi-core versions of the reconfigurable computing platforms are compared with three GPU-based implementations of the algorithm on as many NVIDIA computing boards: Jetson Nano, Jetson TX2 and Jetson Xavier NX. Results show that the single-core version of our FPGA-based solution fulfils the real-time requirements of a real-life hyperspectral application using a mid-range Xilinx Zynq-7000 SoC chip (XC7Z020-CLG484). Performance levels of the custom hardware accelerator are above the figures obtained by the Jetson Nano and TX2 boards, and power efficiency is higher for smaller sizes of the image block to be processed. To close the performance gap between our proposal and the Jetson Xavier NX, a multi-core version is proposed. The results demonstrate that a solution based on the use of various instances of the FPGA hardware compressor core achieves similar levels of performance than the state-of-the-art GPU, with better efficiency in terms of processed frames by watt.

scholarly journals Graph Constraint and Collaborative Representation Classifier Steered Discriminative Projection with Applications for the Early Identification of Cucumber Diseases

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1217 ◽  
Author(s):  
Yuhua Li ◽  
Fengjie Wang ◽  
Ye Sun ◽  
Yingxu Wang
Keyword(s):  
Early Identification ◽  
Early Stage ◽  
Dimensional Space ◽  
Decision Criterion ◽  
Hyperspectral Data ◽  
Identification Accuracy ◽  
Collaborative Representation ◽  
Efficient Production ◽  
Spectral Curves ◽  
Low Dimensional

Accurate, rapid and non-destructive disease identification in the early stage of infection is essential to ensure the safe and efficient production of greenhouse cucumbers. Nevertheless, the effectiveness of most existing methods relies on the disease already exhibiting obvious symptoms in the middle to late stages of infection. Therefore, this paper presents an early identification method for cucumber diseases based on the techniques of hyperspectral imaging and machine learning, which consists of two procedures. First, reconstruction fidelity terms and graph constraints are constructed based on the decision criterion of the collaborative representation classifier and the desired spatial distribution of spectral curves (391 to 1044 nm) respectively. The former constrains the same-class and different-class reconstruction residuals while the latter constrains the weighted distances between spectral curves. They are further fused to steer the design of an offline algorithm. The algorithm aims to train a linear discriminative projection to transform the original spectral curves into a low dimensional space, where the projected spectral curves of different diseases own better separation trends. Then, the collaborative representation classifier is utilized to achieve online early diagnosis. Five experiments were performed on the hyperspectral data collected in the early infection stage of cucumber anthracnose and Corynespora cassiicola diseases. Experimental results demonstrated that the proposed method was feasible and effective, providing a maximal identification accuracy of 98.2% and an average online identification time of 0.65 ms. The proposed method has a promising future in practical production due to its high diagnostic accuracy and short diagnosis time.

scholarly journals The Electrophoretic and Spectroscopic Characterization of Hgb M

Blood ◽  
1958 ◽  
Vol 13 (10) ◽  
pp. 936-949 ◽  
Author(s):  
PARK S. GERALD
Keyword(s):  
Relative Concentration ◽  
Spectroscopic Characterization ◽  
Spectroscopic Studies ◽  
Spectral Curves ◽  
Spectral Changes ◽  
Electrophoretic Behavior ◽  
Patient Reported ◽  
High Concentrations

Abstract The hemoglobin (hgb) from a patient with Hgb M disease was resolved into two components by starch block electrophoresis (at pH 7.0-7.2) of the oxidized hemolyzate. One component was identified electrophoretically and spectroscopically as Hgb A, and the other as Hgb M. Methods for the determination of the relative concentration of Hgb M were given. In the patient reported, Hgb M was found to comprise approximately 30 per cent of the total hgb. Spectroscopic studies of electrophoreticably isolated Hgb M demonstrated that both the methgb and the cyanmethgb form were abnormal in their spectral curves. The reactions of the methgb form with low and high concentrations of cyanide were found to differ. The nature of the spectral changes were such as to indicate that some of the heme groups of the methgb form react abnormally and others apparently normally. The electrophoretic behavior of the patient’s hemolyzate after treatment with various combinations of cyanide and ferricyanide was consistent with this hypothesis. The differing reactivity of the heme groups was explained in the light of the biochemical genetics of the abnormal hemoglobins.

Mapping the Friction Coefficient of Asphalt Roads Using Airborne Imaging Spectroscopy

2020 ◽  
Author(s):  
Eyal Ben Dor ◽  
Nimrod Carmon
Keyword(s):  
Friction Coefficient ◽  
Spectral Region ◽  
Imaging Spectroscopy ◽  
Real Life ◽  
Hyperspectral Data ◽  
Measuring System ◽  
Spectral Radiance ◽  
Dynamic Friction ◽  
Internal Validation ◽  
Dynamic Friction Coefficient

<p>The purpose of this study was to evaluate the realistic feasibility of using hyperspectral remote sensing airborne data for mapping asphalt road conditions. We constructed a real-life operational scenario, where the road's dynamic friction coefficient was modeled against the reflectance information extracted from the image. The asphalt pavement's dynamic friction coefficient was measured by a standardized technique, using a Dynatest friction-measuring system. The hyperspectral data were acquired by both the Specim AisaFENIX 1K and Telops Hyper-Cam airborne sensors at a selected study site, with roads characterized by different aging conditions. The spectral radiance data were processed to provide apparent surface reflectance and emissivity using ground calibration targets. Our final dataset was comprised of thousands of clean asphalt pixels coupled with geo-rectified in situ friction measurement points. We deployed a partial least squares regression model with the PARACUDA-II spectral data-mining engine, which uses an automated outlier-detection procedure and dual validation routines—a full cross-validation and an iterative internal validation based on a Latin hypercube sampling algorithm. Our results show prediction capabilities across the visible–near infrared–shortwave infrared (0.4–2.5 mm) spectral region of R<sup>2</sup> = 0.72 for the best available model in internal validation, and across the longwave infrared (7.6–11.4 mm) spectral region of R<sup>2</sup>=0.62  for the best available model in internal validation. Both spectral regions (optical and thermal) maintained high significant results with p < 0.0001. Using spectral assignment analysis, we located the spectral bands with the highest weight in the model, and discuss their possible physical and chemical assignments. The derived model was applied back on the hyperspectral images to predict and map the friction values of every road's pixels in the scene. We conclude that although a relatively strong prediction model can be achieved, the imaging spectroscopy technique from airborne platforms ) may open a new frontier in road safety and present a new capability for the promising airborne technology.</p><p> </p>

Hyperspectral Unmixing Using Statistics of Q Function

2011 ◽  
Vol 403-408 ◽  
pp. 59-63 ◽  
Author(s):  
Muhammad Ahmad ◽  
Ihsan Ul Haq
Keyword(s):  
Pearson Correlation ◽  
Real Life ◽  
Median Number ◽  
Hyperspectral Data ◽  
Absolute Deviation ◽  
Efficient Manner ◽  
Hyperspectral Unmixing ◽  
Complete Work ◽  
Vertex Component Analysis ◽  
Q Function

Proposed technique of hyperspectral unmixing is apparent to implement and compute the results in a very fast and efficient manner. To reducing the computational complexity and to estimation of hyperspectral data we adopted a statistical method of median absolute deviation about median. Number of end-members is enumerating by self iterative subspace projection method which depends on Pearson correlation. The mixing matrix is inferred by using Q function projections. A set of tests with real hyperspectral data evaluates the performance and illustrates the effectiveness of the proposed method. For the evaluation of proposed method, the results are compared with the results of vertex component analysis. The experimental results show the effectiveness of proposed method on hyperspectral unmixing. targets Alunite, Buddingtonite, Calcite, Kaolinite, and Muscovite are detected well and have high spectral similarities. Hyperspectral remote sensing is used in a large array of real life applications e.g. Surveillance, Mineralogy, Physics, and Agriculture. The complete work is prepared by using MATLAB.

scholarly journals Flashback psychopathology in combatants with PTSD

2019 ◽  
Vol 25 (2) ◽  
pp. 115-117
Author(s):  
O. G. Syropyatov ◽  
N. О. Dzeruzhynska ◽  
К. Yu. Marushchenko
Keyword(s):  
Mental Disorders ◽  
Emotional Disorders ◽  
Traumatic Event ◽  
Diagnostic Category ◽  
Real Life ◽  
Armed Forces ◽  
Traumatic Experience ◽  
Diagnostic Feature ◽  
Sleep Inertia ◽  
The Past

Background. Flashback is an artistic technique, primarily in cinema, with a temporary interruption of the narrative sequence in order to show some events in the past. In General psychopathology, flashback is an involuntary and unpredictable revival of traumatic experience through extraordinarily vivid memories lasting from a few seconds to several hours, during which veterans feel that a terrible reality from the past invades their real life. Subjectively, patients describe these conditions in the following phenomena: “war is in the eyes”, “I am here and not here”, scenes of death of a friend, scenes of violence. The boundaries between “that” and actual reality are blurred. Flashbacks are also observed when psychoactive substances are used – hallucinogens and stimulants, as well as alcohol. In narcology by flashback the occurrence of symptoms of intoxication after drug use cessation is meant. Flashbacks are also described in right-sided temporal lobe epilepsy, brain tumors, and other organic brain lesions. The literature suggests that flashbacks are a coping mechanism for coping with stress. At the same time, direct or symbolic reflection of the psychotrauma pattern in the content of recurrent memories is one of the main symptoms of diagnosis of psychogenic mental disorders. Wider psychopathological idea of the flashback evidence of nosological non-specificity of this phenomenon (Voloshin V. M., 2005; Alexander Yu. A., 2008; Zhmurov V. A., 2008; Krylov V. I., 2015). The diagnostic criteria for PTSD in ICD-10 do not distinguish flashback episodes from other mental disorders. In DSM-5, the flashback phenomenon is qualified as a dissociative episode and is considered along with reminiscences, illusions, hallucinations, meaningfully associated with recurrent experiences of psychotraumatic experiences, and is a diagnostic feature. Objective. The aim of the study was to investigate clinical and psychopathological features of flashbacks in the structure of PTSD in combatant soldiers. Materials and methods. Clinical follow-up examination of soldiers-combatants was conducted. With the system approach, we examined and selected according to the inclusion criteria 48combatants-servicemenof Armed Forces of Ukraine, males aged 31±0.7 years using the following study algorithm: 1) all respondents – combatants were tested using the Luscher test to screen for emotional disorders; 2) in the selected group of respondents with emotional disorders, a clinical and psychopathological study was further conducted with the additional use of the symptomatic questionnaire SCL-90-R (The Symptom Checklist-90-Revised) to clarify the main and additional symptoms of PTSD and comorbid psychopathological symptoms. Results. A study using ICD-11 revealed signs of PTSD in examined combatants. It is a disorder that develops after exposure to an extreme threatening or terrifying event or series of events, and is characterized by three “pivotal” manifestations: re-experiencing the traumatic event(s) at the present time in the form of vivid intrusive memories accompanied by fear or horror, flashbacks or nightmares; avoidance of thoughts and memories of the event, or avoidance of activities or situations that reminiscent of the event; a state of subjective sense of continuing threat in the form of hyper-alertness or increased reactions of fright. The revealed profile of symptoms was accompanied by additional permanent and widespread and persistent derangements of regulation, self-assessment and interpersonal functioning. For all combatants surveyed, a new diagnostic category of ICD-11 “Complex PTSD” was used. As noted by V. I. Krylov (2015), the symptoms of re-experiencing (flashbacks) are characterized by two main rows – obsessive and overvalued experiences. We also highlighted the different phenomenology of flashbacks, which have the following differences. First, the obsessive nature of reminiscences is observed in those memories that the patient wants to forget, the leading value in this case is the content of memories. Second, for intrusive ideas the focus is on intense affective images and pictures of psychotraumatic events. Third, retrospective self-analysis of the correctness of their behavior in a psychotraumatic situation has a leading place in obsessive doubts. Fourth, overvalued memories and views from the beginning are arbitrarily and are supported by “brothers in arms”. Overvalued experiences are egosyntonic and identify with personality. The opposite view of the aims and meaning of war causes aggression. “Heroization” of their behavior in military conditions takes place. Fifth, nightmares with scenes of war that end in awakenings or sleep inertia states with disorientation in place and time can be accompanied by aggressive actions. On the basis of phenomenological psychopathological analysis the main characteristics of the phenomenon of flashback were derived: 1) reflection of combat trauma in the content of re-experiencing; 2) spontaneous involuntary occurrence of re-experiencing without external provocation; 3) sensual richness of re-experiencing – visual images of flashback have a bright polychromatic character, auditory images are expressed, olfactory disorders are associated with combat experience (the smell of gunpowder, burning, blood); images of recurrent memories have a complete “military” plot; 4) re-experiencing are affectively saturated and repeat the feelings experienced by the combatant during the battle – it is fear, horror, expressed anxiety and bodily haptic sense of danger; 5) unlike epileptic phenomena, there is invariance of re-experiencing in psychogenic flashbacks. Thus, the classic version of flashback in PTSD is characterized by the following clinical and psychopathological features: sensoralized representations and eidetic images; monomodal images; partial immersion in painful experiences with the preservation of contact with reality; preservation of all kinds of orientation, the absence of amnesia during flashback. In psychotic PTSD, accompanied by confusion, which in foreign literature are considered “dissociative disorders”, there are signs of atypical flashback, requiring a different strategy of patient management. These are the following features: transformation of eidetic images into illusions and hallucinations; polymodality of images; full immersion in painful experiences with the loss of contact with real reality; violation of orientation in place and time; partial amnesia of real events. Conclusions. Phenomenological clinical and psychopathological analysis of flashbacks in PTSD allows not only to estimate the belonging of this disorder to combat mental pathology, but to carry out a differential diagnosis of this phenomenon for more effective assistance to military combatants.

scholarly journals One by One: Accumulating Evidence by using Meta-Analytical Procedures for Single-Case Experiments

2017 ◽  
Vol 19 (1) ◽  
pp. 33-58 ◽  
Author(s):  
Patrick Onghena ◽  
Bart Michiels ◽  
Laleh Jamshidi ◽  
Mariola Moeyaert ◽  
Wim Van den Noortgate
Keyword(s):  
Multilevel Models ◽  
Single Case ◽  
Meta Analysis ◽  
Real Life ◽  
Multilevel Approach ◽  
Life Data ◽  
Real Life Data ◽  
Randomisation Test ◽  
Complementary Techniques ◽  
Definition Of

This paper presents a unilevel and multilevel approach for the analysis and meta-analysis of single-case experiments (SCEs). We propose a definition of SCEs and derive the specific features of SCEs’ data that have to be taken into account when analysing and meta-analysing SCEs. We discuss multilevel models of increasing complexity and propose alternative and complementary techniques based on probability combining and randomisation test wrapping. The proposed techniques are demonstrated with real-life data and corresponding R code.

scholarly journals COMPORTAMENTO ESPECTRAL DE FOLHAS DA CANA-DE-AÇÚCAR NA PRESENÇA DE DÉFICIT HÍDRICO

Irriga ◽  
2018 ◽  
Vol 23 (3) ◽  
pp. 609-621
Author(s):  
Peterson Ricardo Fiorio ◽  
Rubens Duarte Coelho ◽  
Pedro Paulo Silva Barros ◽  
Magda Maria Zuleta Bonilla ◽  
Ana Paula Barbosa Gady
Keyword(s):  
Remote Sensing ◽  
Water Deficit ◽  
Time Domain ◽  
Near Infrared ◽  
Infrared Region ◽  
Biophysical Parameters ◽  
Saccharum Spp ◽  
Spectral Behavior ◽  
Spectral Curves ◽  
Time Domain Reflectometer

COMPORTAMENTO ESPECTRAL DE FOLHAS DA CANA-DE-AÇÚCAR NA PRESENÇA DE DÉFICIT HÍDRICO     PETERSON RICARDO FIORIO1; RUBENS DUARTE COELHO2; PEDRO PAULO DA SILVA BARROS3; MAGDA MARIA ZULETA BONILLA4 E ANA PAULA BARBOSA GADY5   1Prof. Dr., Departamento de Engenharia de Sistemas Agrícolas, Escola Superior de Agricultura “Luiz de Queiroz, Av. Pádua Dias, 11 – CEP: 13418-900, Cx. Postal 9 - Piracicaba – SP ,Brasil,  email: [email protected] 2 Prof. Dr., Departamento de Engenharia de Sistemas Agrícolas, Escola Superior de Agricultura “Luiz de Queiroz, Av. Pádua Dias, 11 - CEP: 13418-900, Cx. Postal 9 - Piracicaba – SP, Brasil,  email: [email protected] 3Pós Doutorando, Departamento de Engenharia de Sistemas Agrícolas, Escola Superior de Agricultura “Luiz de Queiroz, Av. Pádua Dias, 11 - CEP: 13418-900, Cx. Postal 9 - Piracicaba – SP, Brasil,  email: [email protected] 4Mestra, Departamento de Engenharia de Sistemas Agrícolas, Escola Superior de Agricultura “Luiz de Queiroz, Av. Pádua Dias, 11 - Cx. Postal 9 - CEP: 13418-900, Piracicaba – SP, Brasil,  email: [email protected] 5Pós Doutora, Departamento de Engenharia de Sistemas Agrícolas, Escola Superior de Agricultura “Luiz de Queiroz, Av. Pádua Dias, 11 - CEP: 13418-900, Cx. Postal 9 - Piracicaba – SP, Brasil,  email: [email protected]     1 RESUMO   O sensoriamento remoto é uma das ferramentas disponíveis atualmente aos agricultores que permite quantificar a variabilidade espacial do estado hídrico da vegetação de maneira rápida, uma vez que é uma técnica não destrutiva e de ampla abrangência para a quantificação de parâmetros biofísicos. Neste contexto, o objetivo do presente estudo foi identificar o efeito do déficit hídrico no comportamento espectral de folhas de cana-de-açúcar. O estudo foi realizado em ambiente protegido (casa de vegetação), conduzido em delineamento em blocos ao acaso (DBC), sendo os tratamentos distribuídos em três blocos, totalizando, cinco tratamentos repetidos três vezes, para um total de 60 caixas. A irrigação de cada tratamento foi feita com base na evapotranspiração acumulada (EToAc) e a umidade do solo foi monitorada utilizando tensiometria e TDR (Time Domain Reflectometer). As leituras espectrais foram realizadas utilizando o espectrorradiômetro ASD FieldSpec 3, nas quais foram mensuradas quatro plantas por caixa. Com base nos dados analisados foi possível observar variações na intensidade da reflectância entre os tratamentos quando o déficit hídrico foi imposto. Concluiu-se que as curvas espectrais dos tratamentos com mais dias após o término da irrigação apresentam reflectância mais alta, principalmente na região do infravermelho próximo.   Palavras-chave: sensoriamento remoto hiperespectral; estresse hídrico; comportamento espectral; irrigação; saccharum spp.     FIORIO, P. R.; COELHO, R. D.; BARROS, P. P. S.; BONILLA, M. M. Z.; GADY, A. P. B. SPECTRAL BEHAVIOR OF SUGARCANE'S LEAVES UNDER THE WATER DEFICIT CONDITIONS     2 ABSTRACT   The remote sensing nowadays is an available tool for farmers that allows they quantify space variability of water vegetation state, since it is a non-destructive technique and broad fullness for quantification of vegetation biophysical parameters. In this context, the aim of this study was identify the effect of water deficit in the spectral behavior of sugarcane's leaves. The study was realized inside of protected environment (greenhouse), managing randomized blocks design (RBD), the treatments were distributed on three blocks, totalizing five treatments repeated three times by 60 boxes. The irrigation of each treatment was performed based on the accumulated evapotranspiration (ETc) and the soil humidity was monitoring by tensiometers and TDR (Time Domain Reflectometer). Spectral data were collected using ASD FieldSpec 3 spectroradiometer, it was measured four plants in each box. Based on the analyzed data it was possible observe variations in the intensity of reflectance while the water deficit was imposed. In conclusion the spectral curves of treatments with more days after finished of irrigation show highest reflectance, mainly in near infrared region.   Keywords: hyperspectral remote sensing; water stress; spectral behavior; irrigation; saccharum spp.

scholarly journals Compressed Sensing Technology for Spectral Reconstruction Based on Maximum Entropy Criterion

2021 ◽  
Author(s):  
Shoubo Zhao ◽  
Mengyu Yang ◽  
Yang Wang ◽  
Jianying Fan
Keyword(s):  
Compressed Sensing ◽  
Maximum Entropy ◽  
Spectral Reflectance ◽  
Spectral Curve ◽  
Hyperspectral Data ◽  
Threshold Method ◽  
Data Set ◽  
Spectral Curves ◽  
Sensing Technology ◽  
Entropy Criterion

Abstract In order to choose the related sampling ratio in the information-poor and information-rich spectral fragments, this paper attempts to recover the spectral reflectance by compressed sensing technology based on maximum entropy criterion. The maximum entropy threshold method is the criterion that the optimal threshold is determined to segment the information content of spectral curves. The spectral reflectance in each sub-spectral fragment is reconstructed by compressed sensing. The wavelet orthogonal matrix performs a sparse representation of each segmented spectral curve. Undersampling spectral curve be collected by random gaussian measurement matrix. The orthogonal matching pursuit algorithm recovers sparse original signals from undersampling observed signals. In this paper, the four standard color blocks of Munsell and the spectral curves of five types of ground objects in the hyperspectral data set are used as the exper-imental objects. The reconstructed results are evaluated by spectral curve reconstruction, root mean square error and information entropy difference. The experimental results show that our approach improves the reconstruction accuracy of spectral reflectance effectively, compared with the traditional method.

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