- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Enhancement of objects in photoacoustic tomography using selective filtering
摘要： Here we developed a real-time photoacoustic tomography (PAT) imaging acquisition device based on the linear array transducer utilized on ultrasonic devices. Also, we produced a phantom including diverse contrast media and acquired PAT imaging as the light source wavelength was changing to see if the contrast media reacted. Indocyanine green showed the highest reaction around the 800-nm band, methylene blue demonstrated the same in the 750-nm band, and gold nanoparticle showed the same in the 700-nm band. However, in the case of superparamagnetic iron oxide, we observed not reaction within the wavelength bands used herein to obtain imaging. Moreover, we applied selective filtering to the acquired PAT imaging to remove noise from around and reinforce the object’s area. Consequentially, we could see the object area in the imaging was effectively detected and the image noise was removed.
关键词： Photoacoustic image,real-time,back projection algorithm,selective filtering,ultrasonic imaging
更新于2025-09-23 15:23:52
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Effect of Non-Uniform Azimuth Sampling on Sar Image Formation Evaluated at 79Ghz
摘要： Conventional synthetic aperture radar (SAR) image formation requires uniform sampling along the azimuth direction. These image formation relies on frequency domain algorithms including the Range-Doppler Algorithm (RDA), Chirp-Scaling Algorithm (CSA) [1] etc, that make use of azimuth Fast Fourier Transform, hence the requirement of uniform sampling. While uniform sampling in space is not always achievable, the samples can be interpolated onto a uniform grid given the sampling rate is Nyquist. This paper studies the effect of SAR image formation when the azimuth sampling is not uniform, and not Nyquist in some interval. The results showed that even if there is a wide interval in the middle of the synthetic aperture with no samples, an image can still be formed. This result could be useful when the SAR antenna is a phased array, or when the hardware is generating bursts of pulses followed by a quiet window.
关键词： Image focusing,Back-Projection,Azimuth Sampling,Synthetic aperture radar
更新于2025-09-23 15:22:29
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[IEEE 2019 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO) - Zhenjiang, China (2019.8.4-2019.8.8)] 2019 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO) - Modification of Wettability Property of NITI Alloy by Laser Texturing and Carbon Ion Implantation
摘要： Nonlocal self-similarity of images has attracted considerable interest in the field of image processing and has led to several state-of-the-art image denoising algorithms, such as block matching and 3-D, principal component analysis with local pixel grouping, patch-based locally optimal wiener, and spatially adaptive iterative singular-value thresholding. In this paper, we propose a computationally simple denoising algorithm using the nonlocal self-similarity and the low-rank approximation (LRA). The proposed method consists of three basic steps. First, our method classifies similar image patches by the block-matching technique to form the similar patch groups, which results in the similar patch groups to be low rank. Next, each group of similar patches is factorized by singular value decomposition (SVD) and estimated by taking only a few largest singular values and corresponding singular vectors. Finally, an initial denoised image is generated by aggregating all processed patches. For low-rank matrices, SVD can provide the optimal energy compaction in the least square sense. The proposed method exploits the optimal energy compaction property of SVD to lead an LRA of similar patch groups. Unlike other SVD-based methods, the LRA in SVD domain avoids learning the local basis for representing image patches, which usually is computationally expensive. The experimental results demonstrate that the proposed method can effectively reduce noise and be competitive with the current state-of-the-art denoising algorithms in terms of both quantitative metrics and subjective visual quality.
关键词： self-similarity,Back projection,patch grouping,image denoising,low-rank approximation (LRA),singular value decomposition (SVD)
更新于2025-09-23 15:21:01
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[IEEE 2018 International Electronics Symposium on Engineering Technology and Applications (IES-ETA) - Bali Island, Indonesia (2018.10.29-2018.10.30)] 2018 International Electronics Symposium on Engineering Technology and Applications (IES-ETA) - Vein Visualization System Using Camera and Projector Based on Distance Sensor
摘要： The location of the veins of every person is different, some are visible with the naked eye and some are invisible. This is due to the location of the veins deep below the skin, usually due to excessive fat covered. Many papers that have the topic to solve this difficulty mostly perform only image processing without back-projection. In this paper, we propose a method for improving vein image enhancement using high boost filter and preliminary study about back projection by using the intersection between camera view and projector view. Vein data acquired by NIR reflection method. The obtained vein image enhanced by using a high-boost filter. To deal with the post-segmentation noise, we use a combination of morphology and contour area. Based on these combinations, the accuracy of vein detection is 84.62%. The result of the preliminary study about back-projection is already able to project the vein image and the future work is focused on adjusting the projection in term of distance change between device and object.
关键词： image processing,high boost filter,contour area,vein pattern,intravenous access,NIR,back-projection
更新于2025-09-19 17:15:36
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[IEEE 2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring) - Rome, Italy (2019.6.17-2019.6.20)] 2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring) - A Singular Value Decomposition Based Approach for Classifying Concealed Objects in Short Range Polarimetric Radar Imaging
摘要： In current research one of the main challenges in short range synthetic aperture radar (SAR) is electrically small structures and objects, which tend to unclear reinforced or through the wall objects, object orientation angle, and obscure contribution to extract the position of concealed multiple small objects. In this paper, ultra-wide-band (UWB) polarimetric radar was used to study reinforced objects and for estimation of object angle at short range. Electrically small 1D periodic mesh, 2D periodic meshes and di?erently oriented small objects or meshes could not be distinguished in conventional SAR images. A radar system with transmit and receive antennae mounted on a two dimensional scanning grid was used. The aim is non-destructive testing of built structures, in concrete slab manufacturing and for use in the renovation process. UWB short range radar data and images corresponding to di?erent polarization states were analysed by using singular value decomposition (SVD). To perform decomposition, the proposed approach applies SVD to image data matrices produced from the back projection algorithm (BPA) to classify the di?erent objects and identify the object angle. Then, sets of singular-components of di?erent polarization states are analysed to classify objects. Also, the BPA algorithm is performed to construct the object images from the polarimetric radar signals. The object re?ection varied with the polarimetric state of the UWB radar, which contributes to di?erent object signatures (i.e., object intensity) since the object signature depends on the orientation, the size, and the number of objects. Object orientation with respect to the radar system and object anisotropy could be determined from the ratio of the di?erent polarimetric singular-components. This proposed complex data analysis method demonstrates the usefulness of the SVD using BPA in extracting more information about and for classifying an object.
关键词： back projection algorithm (BPA),object classification,ultra-wide-band (UWB) polarimetric radar,Synthetic aperture radar (SAR),singular value decomposition (SVD)
更新于2025-09-19 17:13:59
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[IEEE 2019 Days on Diffraction (DD) - St. Petersburg, Russia (2019.6.3-2019.6.7)] 2019 Days on Diffraction (DD) - Novel types of mode dispersion of optical vortices in twisted optical fibers
摘要： Nonlocal self-similarity of images has attracted considerable interest in the field of image processing and has led to several state-of-the-art image denoising algorithms, such as block matching and 3-D, principal component analysis with local pixel grouping, patch-based locally optimal wiener, and spatially adaptive iterative singular-value thresholding. In this paper, we propose a computationally simple denoising algorithm using the nonlocal self-similarity and the low-rank approximation (LRA). The proposed method consists of three basic steps. First, our method classifies similar image patches by the block-matching technique to form the similar patch groups, which results in the similar patch groups to be low rank. Next, each group of similar patches is factorized by singular value decomposition (SVD) and estimated by taking only a few largest singular values and corresponding singular vectors. Finally, an initial denoised image is generated by aggregating all processed patches. For low-rank matrices, SVD can provide the optimal energy compaction in the least square sense. The proposed method exploits the optimal energy compaction property of SVD to lead an LRA of similar patch groups. Unlike other SVD-based methods, the LRA in SVD domain avoids learning the local basis for representing image patches, which usually is computationally expensive. The experimental results demonstrate that the proposed method can effectively reduce noise and be competitive with the current state-of-the-art denoising algorithms in terms of both quantitative metrics and subjective visual quality.
关键词： patch grouping,Back projection,low-rank approximation (LRA),singular value decomposition (SVD),image denoising,self-similarity
更新于2025-09-19 17:13:59
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Toroidally focused sensor array for real-time laser-ultrasonic imaging: the first experimental study
摘要： In this paper we report on the first toroidally focused 2D real-time laser-ultrasonic imaging system and a modified filtered back projection algorithm that can be used in the region near the waist of the astigmatic laser-ultrasonic probe beam. The system is capable of visualizing an acupuncture needle 0.2 mm in diameter located at ~4 cm depth in water. The lateral spatial resolution is better than ~0.32 mm and axial spatial resolution is ~30 μm. The achieved frame rate is up to 30 Hz. The depth dependency of the sensitivity region width and lateral resolution are experimentally measured and discussed. The array is intended to be used as a part of combined real-time photoacoustic and laser-ultrasonic imaging system.
关键词： laser ultrasound imaging,back projection,tomography,real-time,focused array,laser ultrasound,toroidal array
更新于2025-09-16 10:30:52
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - High Quality Isar Imaging for Target of Arbitrary Trajectory Based on Back Projection and Particle Swarm Optimization
摘要： When the target has large size or the target moves irregularly, traditional inverse synthetic aperture radar (ISAR) imaging method will lead to a poor image quality due to space variate and migration of echo envelop. In this paper, a novel method based on Back Projection (BP) and Particle Swarm Optimization (PSO) is proposed, which can achieve high quality images under the circumstances of irregular motion, large target and low signal to noise ratio (SNR). First, Target motion is modeled as a turntable, then the translational motion and rotational motion are modeled as two polynomials. Entropy of coherent superposition value of part of the imaging scene pixels based on BP algorithm is utilized as the evaluation function to estimate the polynomial coefficients based on an optimization algorithm such as PSO. Once the polynomial coefficients are estimated, a high quality image of the whole scene can be obtained by BP algorithm. The simulation results verify the effectiveness of the proposed method.
关键词： Back Projection (BP),particle swarm optimization (PSO),Inverse synthetic aperture radar (ISAR)
更新于2025-09-10 09:29:36
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Relating Sar Tomography to Tropical Forest Biomass Via Lidar Data
摘要： Forest biomass is a most important parameter in the context of the global carbon cycle. Mapping above ground biomass (AGB) at a global scale contributes to understanding the dynamics of climate change. Tropical forests are extremely important as they store more biomass. In recent years, SAR tomography has been introduced as a new technique that has shown enormous potential in AGB retrieval. A strong linear relationship between in-situ measurements and tomographic power from 30 m above the terrain was discovered by previous studies carried out in French Guiana. However, the two parameters that determine the linear relationship might vary for different tropical forests. Due to the great difficulty in measuring tropical forest AGB by field surveys, in-situ measurements is unfeasible to relate SAR tomography for mapping global forests AGB. For purpose of solving this problem, we investigate the possibility to use LiDAR derived AGB to find the two parameters of the fit line. Experimental results obtained by processing data from the TropiSAR campaign support the feasibility of the proposed concept.
关键词： Tropical Forest,SAR Tomography,Biomass,LiDAR,Back-projection
更新于2025-09-09 09:28:46
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - A Novel Imaging Formation of Electromagnetic Vortex Sar with Time-Variant Orbital-Angular-Momentum
摘要： In recent years, electromagnetic vortex waves carrying orbital angular momentum (OAM) arouse extensive attention in remote sensing imaging fields. However, most of the researches concentrate on the staring imaging mode, where the radar is motionless relative to the targets. We establish a novel system operation mode based on the principle of synthetic aperture radar (SAR). The echo model upon this novel operation mode is established and the new imaging method modified from the back-projection (BP) algorithm is deduced. Simulation and image evaluation results demonstrate the validation of the proposed method and OAM-based SAR system can be utilized in the SAR data acquisition and signal processing fields.
关键词： Orbital angular momentum (OAM),back-projection (BP) algorithm,synthetic aperture radar (SAR),electromagnetic (EM) vortex
更新于2025-09-09 09:28:46