Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (6)
  • Open Access


    PAN-DeSpeck: A Lightweight Pyramid and Attention-Based Network for SAR Image Despeckling

    Saima Yasmeen1, Muhammad Usman Yaseen1,*, Syed Sohaib Ali2, Moustafa M. Nasralla3, Sohaib Bin Altaf Khattak3

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3671-3689, 2023, DOI:10.32604/cmc.2023.041195

    Abstract SAR images commonly suffer from speckle noise, posing a significant challenge in their analysis and interpretation. Existing convolutional neural network (CNN) based despeckling methods have shown great performance in removing speckle noise. However, these CNN-based methods have a few limitations. They do not decouple complex background information in a multi-resolution manner. Moreover, they have deep network structures that may result in many parameters, limiting their applicability to mobile devices. Furthermore, extracting key speckle information in the presence of complex background is also a major problem with SAR. The proposed study addresses these limitations by introducing a lightweight pyramid and attention-based… More >

  • Open Access


    Deep Feature Bayesian Classifier for SAR Target Recognition with Small Training Set

    Liguo Zhang1,2, Zilin Tian1, Yan Zhang3,*, Tong Shuai4, Shuo Liang4, Zhuofei Wu5

    Journal of New Media, Vol.4, No.2, pp. 59-71, 2022, DOI:10.32604/jnm.2022.029360

    Abstract In recent years, deep learning algorithms have been popular in recognizing targets in synthetic aperture radar (SAR) images. However, due to the problem of overfitting, the performance of these models tends to worsen when just a small number of training data are available. In order to solve the problems of overfitting and an unsatisfied performance of the network model in the small sample remote sensing image target recognition, in this paper, we uses a deep residual network to autonomously acquire image features and proposes the Deep Feature Bayesian Classifier model (RBnet) for SAR image target recognition. In the RBnet, a… More >

  • Open Access


    An Improved Range Doppler Algorithm Based on Squint FMCW SAR Imaging

    Qi Chen, Wei Cui*, Jianqiu Sun, Xingguang Li, Xuyu Tian

    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 115-126, 2021, DOI:10.32604/iasc.2021.011617

    Abstract The existing range-Doppler algorithms for SAR imaging are affected by a fast-time Doppler effect so they cannot be directly applied to FMCW SAR. Moreover, range migration is more evident in squint mode. To reveal the influence of the continuous motion of FMCW SAR in the squint mode on the echo signal and optimize the imaging process, an improved range-Doppler algorithm is based on squint FMCW SAR imaging is proposed in this paper. Firstly, the imaging geometry model and echo signal model of FMCW SAR are analyzed and deduced. The problem of Doppler center offset under squint mode is eliminated by… More >

  • Open Access


    New SAR Imaging Algorithm via the Optimal Time-Frequency Transform Domain

    Zhenli Wang1, *, Qun Wang1, Jiayin Liu1, Zheng Liang1, Jingsong Xu2

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2351-2363, 2020, DOI:10.32604/cmc.2020.011909

    Abstract To address the low-resolution imaging problem in relation to traditional Range Doppler (RD) algorithm, this paper intends to propose a new algorithm based on Fractional Fourier Transform (FrFT), which proves highly advantageous in the acquisition of high-resolution Synthetic Aperture Radar (SAR) images. The expression of the optimal order of SAR range signals using FrFT is deduced in detail, and the corresponding expression of the azimuth signal is also given. Theoretical analysis shows that, the optimal order in range (azimuth) direction, which turns out to be very unique, depends on the known imaging parameters of SAR, therefore the engineering practicability of… More >

  • Open Access


    High Resolution SAR Image Algorithm with Sample Length Constraints for the Range Direction

    Zhenli Wang1, *, Qun Wang1, Fujuan Li1, Shuai Wang2

    CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1533-1543, 2020, DOI:10.32604/cmc.2020.09721

    Abstract The traditional Range Doppler (RD) algorithm is unable to meet practical needs owing to the limit of resolution. The order of fractional Fourier Transform (FrFT) and the length of sampling signals affect SAR imaging performance when FrFT is applied to RD algorithm. To overcome the above shortcomings, the purpose of this paper is to propose a high-resolution SAR image algorithm by using the optimal order of FrFT and the sample length constraints for the range direction. The expression of the optimal order of SAR range signals via FrFT is deduced in detail. The initial sample length and its constraints are… More >

  • Open Access


    Frequency Domain Filtering SAR Interferometric Phase Noise Using the Amended Matrix Pencil Model

    Y,ong Gao1, Shubi Zhang1,*, Kefei Zhang2,*, Shijin Li1

    CMES-Computer Modeling in Engineering & Sciences, Vol.119, No.2, pp. 349-363, 2019, DOI:10.32604/cmes.2019.03943

    Abstract Interferometric phase filtering is one of the key steps in interferometric synthetic aperture radar (InSAR/SAR). However, the ideal filtering results are difficult to obtain due to dense fringe and low coherence regions. Moreover, the InSAR/SAR data range is relatively large, so the efficiency of interferential phase filtering is one of the major problems. In this letter, we proposed an interferometric phase filtering method based on an amended matrix pencil and linear window mean filter. The combination of the matrix pencil and the linear mean filter are introduced to the interferometric phase filtering for the first time. First, the interferometric signal… More >

Displaying 1-10 on page 1 of 6. Per Page