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  • Open Access


    Enhancing Hyper-Spectral Image Classification with Reinforcement Learning and Advanced Multi-Objective Binary Grey Wolf Optimization

    Mehrdad Shoeibi1, Mohammad Mehdi Sharifi Nevisi2, Reza Salehi3, Diego Martín3,*, Zahra Halimi4, Sahba Baniasadi5

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3469-3493, 2024, DOI:10.32604/cmc.2024.049847

    Abstract Hyperspectral (HS) image classification plays a crucial role in numerous areas including remote sensing (RS), agriculture, and the monitoring of the environment. Optimal band selection in HS images is crucial for improving the efficiency and accuracy of image classification. This process involves selecting the most informative spectral bands, which leads to a reduction in data volume. Focusing on these key bands also enhances the accuracy of classification algorithms, as redundant or irrelevant bands, which can introduce noise and lower model performance, are excluded. In this paper, we propose an approach for HS image classification using… More >

  • Open Access


    Hyperspectral Image Based Interpretable Feature Clustering Algorithm

    Yaming Kang1,*, Peishun Ye1, Yuxiu Bai1, Shi Qiu2

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2151-2168, 2024, DOI:10.32604/cmc.2024.049360

    Abstract Hyperspectral imagery encompasses spectral and spatial dimensions, reflecting the material properties of objects. Its application proves crucial in search and rescue, concealed target identification, and crop growth analysis. Clustering is an important method of hyperspectral analysis. The vast data volume of hyperspectral imagery, coupled with redundant information, poses significant challenges in swiftly and accurately extracting features for subsequent analysis. The current hyperspectral feature clustering methods, which are mostly studied from space or spectrum, do not have strong interpretability, resulting in poor comprehensibility of the algorithm. So, this research introduces a feature clustering algorithm for hyperspectral… More >

  • Open Access


    Three-Stages Hyperspectral Image Compression Sensing with Band Selection

    Jingbo Zhang, Yanjun Zhang, Xingjuan Cai*, Liping Xie*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 293-316, 2023, DOI:10.32604/cmes.2022.020426

    Abstract Compressed sensing (CS), as an efficient data transmission method, has achieved great success in the field of data transmission such as image, video and text. It can robustly recover signals from fewer Measurements, effectively alleviating the bandwidth pressure during data transmission. However, CS has many shortcomings in the transmission of hyperspectral image (HSI) data. This work aims to consider the application of CS in the transmission of hyperspectral image (HSI) data, and provides a feasible research scheme for CS of HSI data. HSI has rich spectral information and spatial information in bands, which can reflect… More >

  • Open Access


    Hyperspectral Reflectance Imaging for Detecting Typical Defects of Durum Kernel Surface

    Feng-Nong Chena,b#, Pu-Lan Chenc#, Kai Fana, Fang Chengd

    Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 351-358, 2018, DOI:10.1080/10798587.2017.1293927

    Abstract In recent years, foodstuff quality has triggered tremendous interest and attention in our society as a series of food safety problems. The hyperspectral imaging techniques have been widely applied for foodstuff quality. In this study, we were undertaken to explore the possibility of unsound kernel detecting (Triticum durum Desf), which were defined as black germ kernels, moldy kernels and broken kernels, by selecting the best band in hyperspectral imaging system. The system possessed a wavelength in the range of 400 to 1,000  nm with neighboring bands 2.73  nm apart, acquiring images of bulk wheat samples… More >

  • Open Access


    Waveband Selection with Equivalent Prediction Performance for FTIR/ATR Spectroscopic Analysis of COD in Sugar Refinery Waste Water

    Jun Xie1, Dapeng Sun1, Jiaxiang Cai2, Fuhong Cai1,*

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 687-695, 2019, DOI:10.32604/cmc.2019.03658

    Abstract The level of chemical oxygen demand (COD) is an important index to evaluate whether sewage meets the discharge requirements, so corresponding tests should be carried out before discharge. Fourier transform infrared spectroscopy (FTIR) and attenuated total reflectance (ATR) can detect COD in sewage effectively, which has advantages over conventional chemical analysis methods. And the selection of characteristic bands was one of the key links in the application of FTIR/ATR spectroscopy. In this work, based on the moving window partial least-squares (MWPLS) regression to select a characteristic wavelength, a method of equivalent wavelength selection was proposed More >

  • Open Access


    Band Selection Method of Absorption Peak Perturbance for the FTIR/ATR Spectrum Analysis

    Jun Xie1, Chong Wang1, Jiaxiang Cai2, Fuhong Cai1,*

    CMC-Computers, Materials & Continua, Vol.57, No.2, pp. 261-268, 2018, DOI:10.32604/cmc.2018.03669

    Abstract The rapid quantification method of human serum glucose was established by using the Fourier transform infrared spectroscopy (FTIR) and attenuated total reflection (ATR). By the subtracted spectra between glucose aqueous solution and de-ionized water, absorption peaks are calculated in fingerprint area. Based on these absorption peaks and multiple linear regression (MLR) model, discrete band selection method of absorption peaks disturbance model (APDM) was developed. 5 absorption peaks 1150 cm-1, 1103 cm-1, 1078 cm-1, 1034 cm-1, 991 cm-1 were found in fingerprint area. Used these absorption peaks to establish absorption peaks disturbance model, the optimal wavelength combinations are 1140 More >

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