The airborne and satellite-based synthetic aperture radar enables the acquisition of high-resolution SAR oceanographic images in which even outlines ships can be identified. detection ship targets from has a wide range applications. Due to density images, extreme imbalance between foreground background clutter, diversity target sizes, achieving lightweight highly accurate multi-scale remains great challenge. To this end, paper proposed an attention mechanism for receptive fields convolution...

Detection and localization of stationary targets behind walls is primarily challenged by the presence overwhelming electromagnetic signature front wall in radar returns. In this paper, we use discrete prolate spheroidal sequences to represent spatially extended targets, including exterior walls. This permits formation a linear block sparse model relating range profile observation vectors. Effective clutter suppression can then be performed prior signal image reconstruction. We consider...

As an outstanding method for ocean monitoring, synthetic aperture radar (SAR) has received much attention from scholars in recent years. With the rapid advances field of SAR technology and image processing, significant progress also been made ship detection images. When dealing with large-scale ships on a wide sea surface, most existing algorithms can achieve great results. However, small images contain little feature information. It is difficult to differentiate them background clutter,...

Traditional range-instantaneous Doppler (RID) methods for maneuvering target imaging suffer from the problems of low resolution and poor noise suppression. We propose a new super-resolution inverse synthetic aperture radar (ISAR) method based on deep-learning-assisted time–frequency analysis (TFA). Our deep neural network resembles basic structure U-net with two additional convolutional-upsampling layers <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML"...

We consider sparsity-driven joint localization of stationary and moving targets inside enclosed structures using a reduced set spatial-fast time-slow time observations in ultra-wideband (UWB) pulsed radar platforms. exploit the compact temporal support UWB signal to suppress front wall clutter through gating. The resulting enhancement signal-to-clutter ratio enables application compressive sensing (CS) for scene reconstruction. establish an appropriate model that permits formulation linear...

An approach to remove clouds in Landsat-8 operational land imager (OLI) data was developed with independent component analysis (ICA). Within cloud-covered areas, histograms were derived quantify changes of the reflectance values before and after use algorithm. Referred a cloud-free image, histogram curves validated Scatterplots generated linear regression performed for each band algorithm, compared those reference image. Band-by-band, results cloud removal acceptable. The algorithm had...

Grain number per rice panicle, which directly determines grain yield, is an important agronomic trait for breeding and yield-related research. However, manually counting grains of panicle time-consuming, laborious, error-prone. In this research, a detection model was proposed to automatically recognize count on primary branches panicle. The used image analysis based deep learning convolutional neural network (CNN), by integrating the feature pyramid (FPN) into faster R-CNN network....

The problems that arose in earlier programs to map drainage systems are analyzed detail. An expert system called the Network Extraction System (DNESYS) is described. It uses both local operator and global reasoning extract networks ridge lines. A stream representation a parameterized directed graph (PDG) constructed model system. construction of begins with an initial pixel labeling procedure. Then, network tracing property measurement procedure converts two-dimensional low-level information...

With the improvement of resolution and image swath, received data amount spaceborne synthetic aperture radar (SAR) system is increasingly large imposes more stringent requirement for satellite payload transmission link. In this paper, a novel multiple elevation beam (MEB) SAR processing scheme are studied to reduce amount. The detailed design main procedures described, explicit mathematic expression derived. Furthermore, an exemplary provided simulation results obtained confirm effectiveness...

This study presents a novel motion parameters estimation technique for moving targets, including those with velocities beyond the Nyquist limit in multi-channel synthetic aperture radar data. The proposed this exploits linear dependence between fold factor of cross-track velocity and slope target trajectory range-compressed azimuth time domain after performing Keystone transformation range frequency domain. ambiguity thus can be overcome. along-track retrieved from chirp rate estimated by...

Abstract Extreme learning machine (ELM) is a recent scheme for single hidden layer feed forward networks (SLFNs). It has attracted much interest in the intelligence and pattern recognition fields with numerous real-world applications. The ELM structure several advantages, such as its adaptability to various problems rapid rate low computational cost. However, it shortcomings following aspects. First, suffers from irrelevant variables input data set. Second, choosing optimal number of neurons...

Hyperspectral image (HSI) is often disturbed by various kinds of noise, which brings great challenges to subsequent applications. Many the existing restoration algorithms do not scale well for HSI with large size. This article proposes a novel mixed-noise removal method size, leveraging superpixel segmentation-based technology and distributed algorithm based on graph signal processing (GSP). First, underlying structure modeled two-layer architecture graph. The upper layer, called skeleton...

Cloud detection in multi-temporal optical remote sensing images is a significant task. In this paper, we proposed an efficient method to coarsely detect the cloud via Mean Shift Detection (MSCD) algorithm, which can work automatically without any reference images. Experimental results on Landsat-8 OLI dataset show effectiveness of method.

In this paper, we consider moving target detection and localization inside enclosed structures for through-the-wall radar imaging urban sensing applications. We exploit the fact that scene is sparse in Doppler domain, on account of presence a few targets an otherwise stationary background. The sparsity property used to achieve efficient joint range-crossrange-Doppler estimation buildings using compressive sensing. establish appropriate signal model permits formulation linear modeling with...

An interferometric synthetic aperture radar (InSAR) phase denoising algorithm using the local sparsity of wavelet coefficients and nonlocal similarity grouped blocks was developed. From Bayesian perspective, double- l 1 norm regularization model that enforces constraints used. Taking advantages between group for shrinkage, proposed effectively filtered noise. Applying method to simulated acquired InSAR data, we obtained satisfactory results. In comparison, outperformed several widely-used...

Based on compressive sensing theory, a new method for high resolution inverse aperture radar (ISAR) imaging of maneuvering target is proposed. In this method, only few measurements in ambiguity function plane are sampled to reconstruct the time-frequency distribution by solving problem using basis pursuit method. With Gaussian window as sampling function, trade-off between cross-term suppression and properly dealt with, proposed obtains clear ISAR image with resolution. The effectiveness...

High-resolution radar imaging will give us detailed information of target, which becomes basic function systems. Improvement image resolution the existing system is also important. Based on deep learning, a new method for super-resolution through-the-radar proposed. A network, called cascade U-net (CU-net), proposed in this paper. The results simulation and real data experiments demonstrate effectiveness our methods.

A novel phase unwrapping method is proposed that can be used in digital holograms, magnetic resonance imaging and synthetic aperture radar interferometry. Phase often an essential task for images with periodic phases, its result directly affects the measurement precision. However, path‐independent unwrapped results generally cannot obtained owing to inconsistencies of gradients, i.e. residues. simple efficient approach provided determine connections opposite‐sign residues by analysing...