• Title/Summary/Keyword: sparse projection

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Transmission waveform design for compressive sensing active sonar using the matrix projection from Gram matrix to identity matrix and a constraint for bandwidth (대역폭 제한 조건과 Gram 행렬의 단위행렬로의 사영을 이용한 압축센싱 능동소나 송신파형 설계)

  • Lee, Sehyun;Lee, Keunhwa;Lim, Jun-Seok;Cheong, Myoung-Jun
    • The Journal of the Acoustical Society of Korea
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    • v.38 no.5
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    • pp.522-533
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    • 2019
  • The compressive sensing model for range-Doppler estimation can be expressed as an under-determined linear system y = Ax. To find the solution of the linear system with the compressive sensing method, matrix A should be sufficiently incoherent and x to be sparse. In this paper, we propose a transmission waveform design method that maintains the bandwidth required by the sonar system while lowering the mutual coherence of the matrix A so that the matrix A is incoherent. The proposed method combines two methods of optimizing the sensing matrix with the alternating projection and suppressing unwanted frequency bands using the DFT (Discrete Fourier Transform) matrix. We compare range-Doppler estimation performance of existing waveform LFM(Linear Frequency Modulated) and designed waveform using the matched filter and the compressive sensing method. Simulation shows that the designed transmission waveform has better detection performance than the existing waveform LFM.

Research on Camouflaged Encryption Scheme Based on Hadamard Matrix and Ghost Imaging Algorithm

  • Leihong, Zhang;Yang, Wang;Hualong, Ye;Runchu, Xu;Dawei, Zhang
    • Current Optics and Photonics
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    • v.5 no.6
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    • pp.686-698
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    • 2021
  • A camouflaged encryption scheme based on Hadamard matrix and ghost imaging is proposed. In the process of the encryption, an orthogonal matrix is used as the projection pattern of ghost imaging to improve the definition of the reconstructed images. The ciphertext of the secret image is constrained to the camouflaged image. The key of the camouflaged image is obtained by the method of sparse decomposition by principal component orthogonal basis and the constrained ciphertext. The information of the secret image is hidden into the information of the camouflaged image which can improve the security of the system. In the decryption process, the authorized user needs to extract the key of the secret image according to the obtained random sequences. The real encrypted information can be obtained. Otherwise, the obtained image is the camouflaged image. In order to verify the feasibility, security and robustness of the encryption system, binary images and gray-scale images are selected for simulation and experiment. The results show that the proposed encryption system simplifies the calculation process, and also improves the definition of the reconstructed images and the security of the encryption system.

Object-aware Depth Estimation for Developing Collision Avoidance System (객체 영역에 특화된 뎁스 추정 기반의 충돌방지 기술개발)

  • Gyutae Hwang;Jimin Song;Sang Jun Lee
    • IEMEK Journal of Embedded Systems and Applications
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    • v.19 no.2
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    • pp.91-99
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    • 2024
  • Collision avoidance system is important to improve the robustness and functional safety of autonomous vehicles. This paper proposes an object-level distance estimation method to develop a collision avoidance system, and it is applied to golfcarts utilized in country club environments. To improve the detection accuracy, we continually trained an object detection model based on pseudo labels generated by a pre-trained detector. Moreover, we propose object-aware depth estimation (OADE) method which trains a depth model focusing on object regions. In the OADE algorithm, we generated dense depth information for object regions by utilizing detection results and sparse LiDAR points, and it is referred to as object-aware LiDAR projection (OALP). By using the OALP maps, a depth estimation model was trained by backpropagating more gradients of the loss on object regions. Experiments were conducted on our custom dataset, which was collected for the travel distance of 22 km on 54 holes in three country clubs under various weather conditions. The precision and recall rate were respectively improved from 70.5% and 49.1% to 95.3% and 92.1% after the continual learning with pseudo labels. Moreover, the OADE algorithm reduces the absolute relative error from 4.76% to 4.27% for estimating distances to obstacles.

Development of Unmatched System Model for Iterative Image Reconstruction for Pinhole Collimator of Imaging Systems in Nuclear Medicine (핀홀콜리메이터를 사용한 핵의학영상기기의 순환적 영상 재구성을 위한 비동일 시스템 모델 개발)

  • Bae, Jae-Keon;Bae, Seung-Bin;Lee, Ki-Sung;Kim, Yong-Kwon;Joung, Jin-Hun
    • Journal of radiological science and technology
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    • v.35 no.4
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    • pp.353-360
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    • 2012
  • Diverse designs of collimator have been applied to Single Photon Emission Computed Tomography (SPECT) according to the purpose of acquisition; thus, it is necessary to reflect geometric characteristic of each collimator for successive image reconstruction. This study carry out reconstruction algorithm for imaging system in nuclear medicine with pinhole collimator. Especially, we study to solve sampling problem which caused in the system model of pinhole collimator. System model for a maximum likelihood expectation maximization (MLEM) was developed based on the geometry of the collimator. The projector and back-projector were separately implemented based on the ray-driven and voxel-driven methods, respectively, to overcome sparse sampling problem. We perform phantom study for pinhole collimator by using geant4 application for tomographic emission(GATE) simulation tool. The reconstructed images show promising results. Designed iterative reconstruction algorithm with unmatched system model effective to remove sampling problem artefact. Proposed algorithm can be used not only for pinhole collimator but also for various collimator system of imaging system in nuclear medicine.