- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
Remote Sensing Image Compression in Visible/Near-Infrared Range Using Heterogeneous Compressive Sensing
摘要： Compressive sensing (CS) framework is very suitable for onboard image compression of high-resolution remote sensing cameras in the visible/near-infrared range (VI/NI-RSC) because it has the low-complexity in the sampling measurement stage. In this paper, we propose a new heterogeneous CS method for VI/NI-RSCs. Different from conventional CS methods evenly allocating sensing resources, the proposed method fully employs texture-feature information of remote sensing images to guide the allocation of sensing resources. More sensing resources are allocated to high-frequency regions, but fewer to low-frequency regions. The heterogeneous distribution of sensing resources obtains high reconstruction quality at the same compression performance, as well as high compression performance at the same level reconstructed quality. The shift of sensing resources is consistent with artificial image interpretations, i.e., human visual characteristics, where high-frequency regions, such as edges and textures, are the principal proof of the ground target identification. Experimental results indicate that the proposed method has better reconstruction quality than conventional CS method where texture-features are not utilized.
关键词： panchromatic images,remote sensing image compression,Heterogeneous compressive sensing (CS)
更新于2025-09-23 15:23:52
-
Nonlocal Compressive Sensing-Based SAR Tomography
摘要： Tomographic synthetic aperture radar (TomoSAR) inversion of urban areas is an inherently sparse reconstruction problem and, hence, can be solved using compressive sensing (CS) algorithms. This paper proposes solutions for two notorious problems in this field. First, TomoSAR requires a high number of data sets, which makes the technique expensive. However, it can be shown that the number of acquisitions and the signal-to-noise ratio (SNR) can be traded off against each other, because it is asymptotically only the product of the number of acquisitions and SNR that determines the reconstruction quality. We propose to increase SNR by integrating nonlocal (NL) estimation into the inversion and show that a reasonable reconstruction of buildings from only seven interferograms is feasible. Second, CS-based inversion is computationally expensive and therefore, barely suitable for large-scale applications. We introduce a new fast and accurate algorithm for solving the NL L1-L2-minimization problem, central to CS-based reconstruction algorithms. The applicability of the algorithm is demonstrated using simulated data and TerraSAR-X high-resolution spotlight images over an area in Munich, Germany.
关键词： interferometric synthetic aperture radar (InSAR),tomographic SAR (TomoSAR),Compressive sensing (CS),nonlocal (NL) filtering
更新于2025-09-23 15:22:29
-
[IEEE 2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC) - Bangalore (2018.2.9-2018.2.10)] 2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC) - Sparse Reconstruction of Hyperspectral Image using Bregman Iterations
摘要： Hyperspectral image processing plays an important role in satellite communication. Hyperspectral Image (HSI) processing requires very high ‘computational resources’ in terms of computational time and storage due to extremely large volumes of data collected by imaging spectrometers on-board the satellite. The bandwidth available to transmit the image data from satellite to the ground station is limited. As a result, Hyperspectral image compression is an active research area in the research community in past few years. The research work in the paper proposes a new scheme, Sparsification of HSI and reconstruction (SHSIR) for the reconstruction of hyperspectral image data acquired in Compressive sensing (CS) fashion. Compressed measurements similar to compressive sensing acquisition are generated using measurement matrices containing gaussian i.i.d entries. Now the reconstruction is solving the constrained optimization problem with non smooth terms. Adaptive Bregman iterations method of multipliers is used to convert the difficult optimization problem into a simple cyclic sequence problem. Experimental results from research work indicates that the proposed method performs better than the other existing techniques.
关键词： SHSIR algorithm,Hyperspectral image (HSI),Compressive sensing (CS)
更新于2025-09-23 15:22:29
-
GB-SAR Interferometry Based on Dimension-Reduced Compressive Sensing and Multiple Measurement Vectors Model
摘要： To reduce the data acquisition time and the high-level sidelobes produced by conventional focusing methods for ground-based synthetic aperture radar interferometry, we present a new method to provide accurate displacement maps based on the dimension-reduced compressive sensing (CS) method combined with the multiple measurement vectors (MMVs) model. The proposed CS method consists in selecting the supported area of targets, estimated by the fast conventional method with undersampled data. The following sparse reconstruction is applied only to the selected areas. The MMV-based approach allows increasing the coherence and the precision of displacement estimates. Two experiments are carried out to assess the performance of the proposed method.
关键词： multiple measurement vectors (MMVs) model,SAR interferometry,Compressive sensing (CS),ground-based synthetic aperture radar (GB-SAR),SAR
更新于2025-09-23 15:22:29
-
[IEEE 2019 24th Microoptics Conference (MOC) - Toyama, Japan (2019.11.17-2019.11.20)] 2019 24th Microoptics Conference (MOC) - Wavelength Characteristics of a Silicon Waveguide Mach-Zehnder Interferometer having a Ce:YIG cladding
摘要： The problem of determining and understanding the nature of buried objects by means of nondestructive and non-invasive techniques represents an interesting issue for a great variety of applications. In this framework, the theory of electromagnetic inverse scattering problems can help in such an issue by starting from the measures of the scattered field collected on a surface. What will be presented in this communication is a two-dimensional (2-D) technique based on the so-called Born approximation (BA) combined with a compressive sensing (CS) approach, in order to improve reconstruction capabilities for a proper class of targets. The use of a multiview-multistatic configuration will be employed together with a multifrequency approach to overcome the limited amount of data due to the single-frequency technique. Therefore, after a first numerical analysis of the performance of the considered algorithm, some numerical examples for 2-D aspect-limited configurations will be presented. The scenario is composed of a simplified scene, which consists of two half-spaces, and with the probes located close to the interface between the two media. As proposed in the following, it is easy to observe that the use of CS for this kind of problems may improve reconstruction capabilities, confirming the validity of the presented approach.
关键词： microwave,scattering,ground penetrating,Compressive sensing (CS),tomography,inverse,electromagnetic radar
更新于2025-09-23 15:19:57
-
Fast Parallel Implementation of Dual-Camera Compressive Hyperspectral Imaging System
摘要： Coded aperture snapshot spectral imager (CASSI) provides a potential solution to recover the 3D hyperspectral image (HSI) from a single 2D measurement. The latest proposed design of dual-camera compressive hyperspectral imager (DC-CHI) can collect more information simultaneously with CASSI to improve the reconstruction quality. The main bottleneck now lies in the high computation complexity of the reconstruction methods, which hinders the practical application. In this paper, we propose a fast parallel implementation based on DCCHI to reach a stable and efficient HSI reconstruction. Specifically, we develop a new optimization method for the reconstruction problem, which integrates the alternative direction multiplier method (ADMM) with the total variation (TV) based regularization to boost the convergence rate. Then, to improve the time efficiency, a novel parallel implementation based on GPU is proposed. The performance of the proposed method is validated on both synthetic and real data. The experiment results demonstrate our method has a significant advantage in time efficiency while maintaining a comparable reconstruction fidelity.
关键词： GPU,fast reconstruction,Compressive sensing (CS),hyperspectral imaging
更新于2025-09-10 09:29:36