scholarly journals Evolutionary Multiobjective Optimization with Endmember Priori Strategy for Large-Scale Hyperspectral Sparse Unmixing

Electronics ◽  
2021 ◽  
Vol 10 (17) ◽  
pp. 2079
Author(s):  
Zhao Wang ◽  
Jinxin Wei ◽  
Jianzhao Li ◽  
Peng Li ◽  
Fei Xie
Keyword(s):  
Multiobjective Optimization ◽  
Large Scale ◽  
High Efficiency ◽  
Hyperspectral Image ◽  
Simulated Data ◽  
Reconstruction Error ◽  
Initial Population ◽  
Spectral Library ◽  
Nondominated Solutions ◽  
Mixed Pixels

Mixed pixels inevitably appear in the hyperspectral image due to the low resolution of the sensor and the mixing of ground objects. Sparse unmixing, as an emerging method to solve the problem of mixed pixels, has received extensive attention in recent years due to its robustness and high efficiency. In theory, sparse unmixing is essentially a multiobjective optimization problem. The sparse endmember term and the reconstruction error term can be regarded as two objectives to optimize simultaneously, and a series of nondominated solutions can be obtained as the final solution. However, the large-scale spectral library poses a challenge due to the high-dimensional number of spectra, it is difficult to accurately extract a few active endmembers and estimate their corresponding abundance from hundreds of spectral features. In order to solve this problem, we propose an evolutionary multiobjective hyperspectral sparse unmixing algorithm with endmember priori strategy (EMSU-EP) to solve the large-scale sparse unmixing problem. The single endmember in the spectral library is used to reconstruct the hyperspectral image, respectively, and the corresponding score of each endmember can be obtained. Then the endmember scores are used as a prior knowledge to guide the generation of the initial population and the new offspring. Finally, a series of nondominated solutions are obtained by the nondominated sorting and the crowding distances calculation. Experiments on two benchmark large-scale simulated data to demonstrate the effectiveness of the proposed algorithm.

scholarly journals Encoding Spectral-Spatial Features for Hyperspectral Image Classification in the Satellite Internet of Things System

2021 ◽  
Vol 13 (18) ◽  
pp. 3561
Author(s):  
Ning Lv ◽  
Zhen Han ◽  
Chen Chen ◽  
Yijia Feng ◽  
Tao Su ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Land Cover ◽  
Image Classification ◽  
Large Scale ◽  
High Efficiency ◽  
Hyperspectral Image ◽  
Remote Sensing Data ◽  
Hyperspectral Images ◽  
Hyperspectral Image Classification ◽  
Spatial Features

Hyperspectral image classification is essential for satellite Internet of Things (IoT) to build a large scale land-cover surveillance system. After acquiring real-time land-cover information, the edge of the network transmits all the hyperspectral images by satellites with low-latency and high-efficiency to the cloud computing center, which are provided by satellite IoT. A gigantic amount of remote sensing data bring challenges to the storage and processing capacity of traditional satellite systems. When hyperspectral images are used in annotation of land-cover application, data dimension reduction for classifier efficiency often leads to the decrease of classifier accuracy, especially the region to be annotated consists of natural landform and artificial structure. This paper proposes encoding spectral-spatial features for hyperspectral image classification in the satellite Internet of Things system to extract features effectively, namely attribute profile stacked autoencoder (AP-SAE). Firstly, extended morphology attribute profiles EMAP is used to obtain spatial features of different attribute scales. Secondly, AP-SAE is used to extract spectral features with similar spatial attributes. In this stage the program can learn feature mappings, on which the pixels from the same land-cover class are mapped as closely as possible and the pixels from different land-cover categories are separated by a large margin. Finally, the program trains an effective classifier by using the network of the AP-SAE. Experimental results on three widely-used hyperspectral image (HSI) datasets and comprehensive comparisons with existing methods demonstrate that our proposed method can be used effectively in hyperspectral image classification.

scholarly journals A Lightweight Hyperspectral Image Anomaly Detector for Real-Time Mission

2019 ◽  
Vol 11 (13) ◽  
pp. 1622
Author(s):  
Ning Ma ◽  
Ximing Yu ◽  
Yu Peng ◽  
Shaojun Wang
Keyword(s):  
Real Time ◽  
Large Scale ◽  
High Efficiency ◽  
Hyperspectral Image ◽  
Characteristic Curve ◽  
Detection Accuracy ◽  
Nsga Ii ◽  
Mixed Precision ◽  
Anomaly Detector ◽  
Point Data

In real-time onboard hyperspectral-image(HSI) anomalous targets detection, processing speed and accuracy are equivalently desirable which is hard to satisfy at the same time. To improve detection accuracy, deep learning based HSI anomaly detectors (ADs) are widely studied. However, their large scale network results in a massive computational burden. In this paper, to improve the detection throughput without sacrificing the accuracy, a pruning–quantization–anomaly–detector (P-Q-AD) is proposed by building an underlying constraint formulation to make a trade-off between accuracy and throughput. To solve this formulation, multi-objective optimization with nondominated sorting genetic algorithm II (NSGA-II) is employed to shrink the network. As a result, the redundant neurons are removed. A mixed precision network is implemented with a delicate customized fixed-point data expression to further improve the efficiency. In the experiments, the proposed P-Q-AD is implemented on two real HSI data sets and compared with three types of detectors. The results show that the performance of the proposed approach is no worse than those comparison detectors in terms of the receiver operating characteristic curve (ROC) and area under curve (AUC) value. For the onboard mission, the proposed P-Q-AD reaches over 4 . 5 × speedup with less than 0 . 5 % AUC loss compared with the floating-based detector. The pruning and the quantization approach in this paper can be referenced for designing the anomalous targets detectors for high efficiency.

The Potential of Photoelectrochemical Carbon Sinks

2018 ◽  
Author(s):  
Matthias May ◽  
Kira Rehfeld
Keyword(s):  
Global Warming ◽  
High Temperature ◽  
Greenhouse Gas ◽  
Large Scale ◽  
High Efficiency ◽  
Carbon Sink ◽  
Solar Fuels ◽  
Negative Emissions ◽  
Viable Approach ◽  
Low Sensitivity

Greenhouse gas emissions must be cut to limit global warming to 1.5-2C above preindustrial levels. Yet the rate of decarbonisation is currently too low to achieve this. Policy-relevant scenarios therefore rely on the permanent removal of CO<sub>2</sub> from the atmosphere. However, none of the envisaged technologies has demonstrated scalability to the decarbonization targets for the year 2050. In this analysis, we show that artificial photosynthesis for CO<sub>2</sub> reduction may deliver an efficient large-scale carbon sink. This technology is mainly developed towards solar fuels and its potential for negative emissions has been largely overlooked. With high efficiency and low sensitivity to high temperature and illumination conditions, it could, if developed towards a mature technology, present a viable approach to fill the gap in the negative emissions budget.<br>

The Potential of Photoelectrochemical Carbon Sinks

2018 ◽  
Author(s):  
Matthias May ◽  
Kira Rehfeld
Keyword(s):  
Global Warming ◽  
High Temperature ◽  
Greenhouse Gas ◽  
Large Scale ◽  
High Efficiency ◽  
Carbon Sink ◽  
Solar Fuels ◽  
Negative Emissions ◽  
Viable Approach ◽  
Low Sensitivity

Greenhouse gas emissions must be cut to limit global warming to 1.5-2C above preindustrial levels. Yet the rate of decarbonisation is currently too low to achieve this. Policy-relevant scenarios therefore rely on the permanent removal of CO<sub>2</sub> from the atmosphere. However, none of the envisaged technologies has demonstrated scalability to the decarbonization targets for the year 2050. In this analysis, we show that artificial photosynthesis for CO<sub>2</sub> reduction may deliver an efficient large-scale carbon sink. This technology is mainly developed towards solar fuels and its potential for negative emissions has been largely overlooked. With high efficiency and low sensitivity to high temperature and illumination conditions, it could, if developed towards a mature technology, present a viable approach to fill the gap in the negative emissions budget.<br>

Peculiarities of the phytosanitary state of pome fruits in industrial horticulture

2020 ◽  
Vol 60 (1) ◽  
pp. 159-168
Author(s):  
V. V. Antonenko ◽  
A. V. Zubkov ◽  
S. N. Kruchina
Keyword(s):  
Mechanism Of Action ◽  
Large Scale ◽  
High Efficiency ◽  
Fruit Trees ◽  
Fruit Crops ◽  
Planting Material ◽  
Relative Safety ◽  
Pome Fruits ◽  
Weed Plants ◽  
Spread Of Infection

Data were obtained on the basis of the results of research carried out on the territory of the educational and experimental farm of the Timiryazev State Agrarian University, in Moscow during 2018-2019. As a result of the surveys, the most dangerous diseases and pests of pome crops on the territory of this farm were established. The most resistant apple and pear varieties to major diseases have been identified. Peculiarities of development of alternariosis on pear are described, the harmfulness of the disease on pear and apple seedlings is noted. A possible role in the transfer of alternariosis infection from garden-protective plantations and weed vegetation to fruit trees was noted. A possible role has been established in the transport of septoriosis, powdery dew infection from dicotyledonous weeds plants. The peculiarities of the spread of infection under the influence of wind direction are noted. The results and peculiarities of the application of various methods of scaring birds in the orchard are presented. As a result of route surveys the most harmful weed plants have been identified. The possibility of using herbicides of different mechanism of action in fruit gardens for weed control has been studied. High efficiency and relative safety of application of herbicides of contact action in nursery fields, operational orchards and for control of piglets on fruit trees are shown. Recommendations are given for the use of soil and systemic herbicides of soil in seedlings beds, the first and second fields of the nursery, as well as in the process of production of large-scale planting material and operational orchards of fruit crops. The safety of the herbicides in question is established when used in accordance with the recommended methods of use.

scholarly journals Functionalization of Congo red dye as a light harvester on solar cell

2020 ◽  
Vol 18 (1) ◽  
pp. 287-294
Author(s):  
Harsasi Setyawati ◽  
Handoko Darmokoesoemo ◽  
Irmina Kris Murwani ◽  
Ahmadi Jaya Permana ◽  
Faidur Rochman
Keyword(s):  
Solar Cell ◽  
Congo Red ◽  
Large Scale ◽  
High Efficiency ◽  
Solar Cell Device ◽  
Dye Sensitized ◽  
Congo Red Dye ◽  
Elemental Analyses ◽  
Red Dye ◽  
Solar Cell Technology

AbstractThe demands of ecofriendly technologies to produce a reliable supply of renewable energy on a large scale remains a challenge. A solar cell based on DSSC (Dye-Sensitized Solar Cell) technology is environmentally friendly and holds the promise of a high efficiency in converting sunlight into electricity. This manuscript describes the development of a light harvester system as a main part of a DSSC. Congo red dye has been functionalized with metals (Fe, Co, Ni), forming a series of complexes that serve as a novel light harvester on the solar cell. Metal-congo red complexes have been characterized by UV-VIS and FTIR spectroscopy, and elemental analyses. The performance of metal complexes in capturing photons from sunlight has been investigated in a solar cell device. The incorporation of metals to congo red successfully improved of the congo red efficiency as follows: Fe(II)-congo red, Co(II)-congo red and Ni(II)-congo red had efficiencies of 8.17%, 6.13% and 2.65%, respectively. This research also discusses the effect of metal ions on the ability of congo red to capture energy from sunlight.

scholarly journals Cluster-Wise Weighted NMF for Hyperspectral Images Unmixing with Imbalanced Data

2021 ◽  
Vol 13 (2) ◽  
pp. 268
Author(s):  
Xiaochen Lv ◽  
Wenhong Wang ◽  
Hongfu Liu
Keyword(s):  
Spatial Information ◽  
Hyperspectral Image ◽  
Imbalanced Data ◽  
Reconstruction Error ◽  
Hyperspectral Data ◽  
Weight Matrix ◽  
Hyperspectral Images ◽  
Mixed Data ◽  
Sparsity Constraints ◽  
Additional Constraints

Hyperspectral unmixing is an important technique for analyzing remote sensing images which aims to obtain a collection of endmembers and their corresponding abundances. In recent years, non-negative matrix factorization (NMF) has received extensive attention due to its good adaptability for mixed data with different degrees. The majority of existing NMF-based unmixing methods are developed by incorporating additional constraints into the standard NMF based on the spectral and spatial information of hyperspectral images. However, they neglect to exploit the nature of imbalanced pixels included in the data, which may cause the pixels mixed with imbalanced endmembers to be ignored, and thus the imbalanced endmembers generally cannot be accurately estimated due to the statistical property of NMF. To exploit the information of imbalanced samples in hyperspectral data during the unmixing procedure, in this paper, a cluster-wise weighted NMF (CW-NMF) method for the unmixing of hyperspectral images with imbalanced data is proposed. Specifically, based on the result of clustering conducted on the hyperspectral image, we construct a weight matrix and introduce it into the model of standard NMF. The proposed weight matrix can provide an appropriate weight value to the reconstruction error between each original pixel and the reconstructed pixel in the unmixing procedure. In this way, the adverse effect of imbalanced samples on the statistical accuracy of NMF is expected to be reduced by assigning larger weight values to the pixels concerning imbalanced endmembers and giving smaller weight values to the pixels mixed by majority endmembers. Besides, we extend the proposed CW-NMF by introducing the sparsity constraints of abundance and graph-based regularization, respectively. The experimental results on both synthetic and real hyperspectral data have been reported, and the effectiveness of our proposed methods has been demonstrated by comparing them with several state-of-the-art methods.

scholarly journals Complete Ring Artifacts Reduction Procedure for Lab-Based X-ray Nano CT Systems

Sensors ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 238
Author(s):  
Jakub Šalplachta ◽  
Tomáš Zikmund ◽  
Marek Zemek ◽  
Adam Břínek ◽  
Yoshihiro Takeda ◽  
...  
Keyword(s):  
High Efficiency ◽  
Image Inpainting ◽  
Simulated Data ◽  
Complementary Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
Detection Accuracy ◽  
Reduction Procedure ◽  
X Ray ◽  
Artifacts Reduction ◽  
Ct Data

In this article, we introduce a new ring artifacts reduction procedure that combines several ideas from existing methods into one complex and robust approach with a goal to overcome their individual weaknesses and limitations. The procedure differentiates two types of ring artifacts according to their cause and character in computed tomography (CT) data. Each type is then addressed separately in the sinogram domain. The novel iterative schemes based on relative total variations (RTV) were integrated to detect the artifacts. The correction process uses the image inpainting, and the intensity deviations smoothing method. The procedure was implemented in scope of lab-based X-ray nano CT with detection systems based on charge-coupled device (CCD) and scientific complementary metal–oxide–semiconductor (sCMOS) technologies. The procedure was then further tested and optimized on the simulated data and the real CT data of selected samples with different compositions. The performance of the procedure was quantitatively evaluated in terms of the artifacts’ detection accuracy, the comparison with existing methods, and the ability to preserve spatial resolution. The results show a high efficiency of ring removal and the preservation of the original sample’s structure.

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