Registration for multisensor or multimodal image pairs with a large degree of distortions is fundamental task many remote sensing applications. To achieve accurate and low-cost registration, we propose multiscale framework unsupervised learning, named MU-Net. Without costly ground truth labels, MU-Net directly learns the end-to-end mapping from to their transformation parameters. stacks several deep neural network (DNN) models on multiple scales generate coarse-to-fine registration pipeline,...

Identifying feature correspondences between multimodal images is facing enormous challenges because of the significant differences both in radiation and geometry. To address these problems, we propose a novel matching method (named R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> FD ) that robust to rotation differences, which consists repeatable detector rotation-invariant descriptor. In first stage, called Multi-channel...

For remote sensing object detection, fusing the optimal feature information automatically and overcoming sensitivity to adapt multi-scale objects remains a significant challenge for existing convolutional neural networks. Given this, we develop network model with an adaptive attention fusion mechanism (AAFM). The is proposed based on backbone of EfficientDet. Firstly, according characteristics distribution in datasets, stitcher applied make one image containing various scales. Such process...

Over the past few decades, with rapid development of global aerospace and aerial remote sensing technology, types sensors have evolved from traditional monomodal (e.g., optical sensors) to new generation multimodal multispectral, hyperspectral, light detection ranging (LiDAR), synthetic aperture radar (SAR) sensors). These advanced devices can dynamically provide various abundant images (MRSIs) different spatial, temporal, spectral resolutions according application requirements. Since then,...

Co-registering the Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 optical data of European Space Agency (ESA) is great importance for many remote sensing applications. However, we find that there are evident misregistration shifts between SAR images directly downloaded from official website. To address that, this paper presents a fast effective registration method two types images. In proposed method, block-based scheme first designed to extract evenly distributed interest points....

Soft actuators offer numerous potential applications; however, challenges persist in achieving a high driving force and fast response speed. In this work, we present the design, fabrication, analysis of soft pneumatic bistable actuator (PBA) mimicking jellyfish subumbrellar muscle motion for waterjet propulsion. Drawing inspiration from jet propulsion characteristics structure, develop an elastic band stretch prebending PBA with simple low inflation cost, exceptional performance, stable...

Building change detection plays an imperative role in urban construction and development. Although the deep neural network has achieved tremendous success remote sensing image building detection, it is still fraught with problem of generating broken boundaries separation dense buildings, which tends to produce saw-tooth boundaries. In this work, we propose a feature decomposition-optimization-reorganization for detection. The main contribution proposed that performs by respectively modeling...

Abstract. Accurate matching of multimodal remote sensing (RS) images (e.g., optical, infrared, LiDAR, SAR, and rasterized maps) is still an ongoing challenge because nonlinear radiometric differences (NRD) between these images. Considering that structural properties are preserved images, this paper proposes a robust method based on multi-directional multi-scale features, which consist two critical steps. Firstly, novel descriptor named the Steerable Filters first- second-Order Channels...

In this letter, a novel method for change detection is proposed using neighbourhood structure correlation. Because features are insensitive to the intensity differences between bi-temporal images, we perform correlation analysis on rather than information. First, extract feature maps by multi-orientated gradient Then, used obtain Neighbourhood Structural Correlation Image (NSCI), which can represent context addition, introduce measure named matching error, be improve Subsequently, model...

Abstract. Registration for multi-sensor or multi-modal image pairs with a large degree of distortions is fundamental task many remote sensing applications. To achieve accurate and low-cost registration, we propose multiscale unsupervised network (MU-Net). Without costly ground truth labels, MU-Net directly learns the end-to-end mapping from to their transformation parameters. performs coarse-to-fine registration pipeline by stacking several deep neural models on multiple scales, which...

The navigation system plays a pivotal role in guiding aircraft along designated routes, ensuring precise and punctual arrival at destinations. integration of scene matching with an inertial enhances the capability providing dependable guarantee for successful accomplishment flight missions. Nonetheless, assuring reliability encounters significant challenges areas characterized by repetitive or weak textures. To tackle these challenges, we propose novel method to assess based on distinctive...

Over the past few decades, with rapid development of global aerospace and aerial remote sensing technology, types sensors have evolved from traditional monomodal (e.g., optical sensors) to new generation multimodal [e.g., multispectral, hyperspectral, light detection ranging (LiDAR) synthetic aperture radar (SAR) sensors]. These advanced devices can dynamically provide various abundant images different spatial, temporal, spectral resolutions according application requirements. Since then, it...

Abstract. Co-Registration of aerial imagery and Light Detection Ranging (LiDAR) data is quilt challenging because the different imaging mechanism causes significant geometric radiometric distortions between such data. To tackle problem, this paper proposes an automatic registration method based on structural features three-dimension (3D) phase correlation. In proposed method, LiDAR point cloud first transformed into intensity map, which used as reference image. Then, we employ Fast operator...

The rapid and explosive growth of remote sensing image dataset (e.g., optical, SAR, LiDAR) promotes the development aerospace industry. However, images with complex coverage scenes are usually captured by either different sensors from perspectives or same sensor in periods [1]. These factors have brought a great challenge to precision co-registration, it is difficult identify fully universal method cope all registration cases. Any kind algorithm needs consider imaging principle, radiometric...

Automatically identifying feature correspondences between multimodal images is facing enormous challenges because of the significant differences both in radiation and geometry. To address these problems, we propose a novel matching method (named R2FD2) that robust to rotation differences. Our R2FD2 conducted two critical contributions, consisting repeatable detector rotation-invariant descriptor. In first stage, called Multi-channel Auto-correlation Log-Gabor (MALG) presented for detection,...

In this letter, a novel method for change detection is proposed using neighborhood structure correlation. Because features are insensitive to the intensity differences between bi-temporal images, we perform correlation analysis on rather than information. First, extract feature maps by multi-orientated gradient Then, used obtain Neighborhood Structural Correlation Image (NSCI), which can represent context addition, introduce measure named matching error be improve Subsequently, model based...

Image digitization and transmission process often subject to outside interference that was easy let the image turn into de-noising image; General made details blurred. Against phenomenon, this paper using "mathematical microscope" said with wavelet transform, according inherent characteristics of human eye's visual. Put a new optimize scan mode coefficients, proposes threshold algorithm. At last, decrease overhead unnecessary coding algorithm; simplified scanning path reduce，decrease...

Co-Registration of aerial imagery and Light Detection Ranging (LiDAR) data is quilt challenging because the different imaging mechanism causes significant geometric radiometric distortions between such data. To tackle problem, this paper proposes an automatic registration method based on structural features three-dimension (3D) phase correlation. In proposed method, LiDAR point cloud first transformed into intensity map, which used as reference image. Then, we employ Fast operator to extract...