A Coarse-to-Fine Registration Strategy for Multi-Sensor Images with Large Resolution Differences

Automatic image registration for multi-sensors has always been an important task for remote sensing applications. However, registration for images with large resolution differences has not been fully considered. A coarse-to-fine registration strategy for images with large differences in resolution is presented. The strategy consists of three phases. First, the feature-base registration method is applied on the resampled sensed image and the reference image. Edge point features acquired from the edge strength map (ESM) of the images are used to pre-register two images quickly and robustly. Second, normalized mutual information-based registration is applied on the two images for more accurate transformation parameters. Third, the final transform parameters are acquired through direct registration between the original high- and low-resolution images. Ant colony optimization (ACO) for continuous domain is adopted to optimize the similarity metrics throughout the three phases. The proposed method has been tested on image pairs with different resolution ratios from different sensors, including satellite and aerial sensors. Control points (CPs) extracted from the images are used to calculate the registration accuracy of the proposed method and other state-of-the-art methods. The feature-based preregistration validation experiment shows that the proposed method effectively narrows the value range of registration parameters. The registration results indicate that the proposed method performs the best and achieves sub-pixel registration accuracy of images with resolution differences from 1 to 50 times

Multiscale Integer Coding and Data Index of 3D Spatial Grid

This paper proposed a multiscale integer coding and index method available for 3D spatial grid area based on the exiting problems of 3D spatial grid.This method used integer to unify coding the region divided by regular grid, formed a tree structure showed the size relationship and scale variation of grid which embodied the spatial relationships in different scale grid:include, be included, adjacent and so on, and achieved the unified integer coding of multi-scale grid in the end.On this basis, a serious of basic operation methods were also studied like:level operation, coordinate transformation operation between coding and grid, parent-unit query and sub-unit query.The contrast experiment was designed to compare this method with 3D R-tree index of Oracle Spatial.The result showed that, multiscale integer coding of 3D spatial grid was superior to the 3D R-tree of Oracle Spatial in data importing, index establishing and region querying, and the efficiency were enhanced about two times, forty-six times and four times respectively

Block adjustment of satellite imagery with line-of-sight vector rectification

Considering the traditional bundle block adjustment of rational function model is highly constrained by small error of attitude and orbit, narrow field camera and good image intersection angle, a block adjustment method of satellite imagery based on line-of-sight vector rectification was presented. Firstly, the light ray of an image point is calculated by using the rational polynomial coefficients attached to the image, and then the pseudo orbit and attitude of sensor is restored when the point was acquired, then an error compensation model is constructed for the virtual orbit and attitude, and finally the model parameters and object coordinates of tie points are solved simultaneously by the least square method. As the compensation model is modelled from the reason of system errors, it can avoid approximation assumptions and constraints of traditional strategy. Several comparative experiments of simulation data, mapping satellite and non-mapping satellite data are designed. The results show that this algorithm can achieve higher accuracy than the traditional method under various severe conditions such as images with large attitude angle error, large field angle and weak intersection angle

An Efficient Integer Coding and Computing Method for Multiscale Time Segment

This article focus on the exist problem and status of current time segment coding, proposed a new set of approach about time segment coding: multi-scale time segment integer coding (MTSIC). This approach utilized the tree structure and the sort by size formed among integer, it reflected the relationship among the multi-scale time segments: order, include/contained, intersection, etc., and finally achieved an unity integer coding processing for multi-scale time. On this foundation, this research also studied the computing method for calculating the time relationships of MTSIC, to support an efficient calculation and query based on the time segment, and preliminary discussed the application method and prospect of MTSIC. The test indicated that, the implement of MTSIC is convenient and reliable, and the transformation between it and the traditional method is convenient, it has the very high efficiency in query and calculating

Removal of Stripes in Remote Sensing Images Based on Statistics Combined with Image Enhancement

A method to remove stripes from remote sensing images is proposed based on statistics and a new image enhancement method. The overall processing steps for improving the quality of remote sensing images are introduced to provide a general baseline. Due to the differences in satellite sensors when producing images, subtle but inherent stripes can appear at the stitching positions between the sensors. These stitchingstripes cannot be eliminated by conventional relative radiometric calibration. The inherent stitching stripes cause difficulties in downstream tasks such as the segmentation, classification and interpretation of remote sensing images. Therefore, a method to remove the stripes based on statistics and a new image enhancement approach are proposed in this paper. First, the inconsistency in grayscales around stripes is eliminated with the statistical method. Second, the pixels within stripes are weighted and averaged based on updated pixel values to enhance the uniformity of the overall image radiation quality. Finally, the details of the images are highlighted by a new image enhancement method, which makes the whole image clearer. Comprehensive experiments are performed, and the results indicate that the proposed method outperforms the baseline approach in terms of visual quality and radiation correction accuracy

Research on the Method of Urban Waterlogging Flood Routing Based on Hexagonal Grid

An evolution of the urban waterlogging flood routing was studied in this paper based on the method of hexagonal grid modeling. Using the method of discrete grid, established an urban geometry model on account of the regular multi-scale discrete grid. With the fusion of 3D topographic survey data and 2D building vector data, formed a regular network model of surface. This model took multi special block into account, such as urban terrain and buildings. On this basis, a method of reverse flow deduction was proposed, which was an inverse computation from the state of flood to the evolution process. That is, based on the water depth of flood, made use of the connectivity with the outfall to calculate the range of water logging, and then implemented the urban waterlogging flood simulation deduction. The test indicated that, this method can implement the evolution of urban waterlogging scenario deduction effectively. And the correlational research could provide scientific basis for urban disaster prevention and emergency decision-making

A spatial multi-scale integer coding method and its application to three-dimensional model organization

With the rapid development of digital earth, smart city, and digital twin technology, the demands of three-dimensional model data’s application is getting higher and higher. These data tend to be multi-objectification, multi-type, multi-scale, complex spatial relationship, and large amount, which brings great challenges to the efficient organization of them. This paper mainly studies the organization of three-dimensional model data, and the main contributions are as follows: 1) A integer coding method of three dimensional multi-scale grid is proposed, which can reduce the four-dimensional (spatial dimension and scale dimension) space into one-dimensional, and has better space and scale clustering characteristics by comparing with various types of grid coding. 2) The binary algebra calculation method is proposed to realize the basic spatial relationship calculation of three-dimensional grid, which has higher spatial relationship computing ability than 3D-Geohash method; 3) The multi-scale integer coding method is applied to the data organization of three-dimensional city model, and the experiment results show that: it is more efficient and stable than the three-dimensional R-tree index and Geohash coding method in the establishment of index and the query of three dimensional space

UAV Remote Sensing Image Automatic Registration Based on Deep Residual Features

With the rapid development of unmanned aerial vehicle (UAV) technology, UAV remote sensing images are increasing sharply. However, due to the limitation of the perspective of UAV remote sensing, the UAV images obtained from different viewpoints of a same scene need to be stitched together for further applications. Therefore, an automatic registration method of UAV remote sensing images based on deep residual features is proposed in this work. It needs no additional training and does not depend on image features, such as points, lines and shapes, or on specific image contents. This registration framework is built as follows: Aimed at the problem that most of traditional registration methods only use low-level features for registration, we adopted deep residual neural network features extracted by an excellent deep neural network, ResNet-50. Then, a tensor product was employed to construct feature description vectors through exacted high-level abstract features. At last, the progressive consistency algorithm (PROSAC) was exploited to remove false matches and fit a geometric transform model so as to enhance registration accuracy. The experimental results for different typical scene images with different resolutions acquired by different UAV image sensors indicate that the improved algorithm can achieve higher registration accuracy than a state-of-the-art deep learning registration algorithm and other popular registration algorithms

G‐quadruplex‐enhanced circular single‐stranded DNA (G4‐CSSD) adsorption of miRNA to inhibit colon cancer progression

Abstract Background Chromosomal heterogeneity leads to the abnormal expression and mutation of tumor‐specific genes. Drugs targeting oncogenes have been extensively developed. However, given the random mutation of tumor suppressor genes, the development of its targeted drugs is difficult. Methods Our early research revealed that artificial circular single‐stranded DNA (CSSD) can restore multiple tumor suppressor genes to inhibit tumor malignant progression by adsorbing miRNA. Here, we improved CSSD to a fully closed single‐stranded DNA with G quadruplex DNA secondary structure (G4‐CSSD), which made G4‐CSSD with higher acquisition rate and decreased degradation. The Cancer Genome Atlas (TCGA) and Human Protein Atlas database were used to predict tumour suppressor genes in colon cancer. Cellular and animal experiments were performed to validate the role of G4‐CSSD in cancer cell progression. Results In colon cancer, we observed the simultaneous low expressions of chloride channel accessory 1 (CLCA1), UDP‐GlcNAc:betaGal beta‐1,3‐N‐acetylglucosaminyltransferase 6 (B3GNT6) and UDP glucuronosyltransferase family 2 member A3 (UGT2A3), which indicated an favourable prognosis. After repressing miR‐590‐3p with G4‐CSSD590, the upregulation of CLCA1, B3GNT6 and UGT2A3 inhibited the proliferation and metastasis of colon cancer cells. Conclusions This study may provide basis for new treatment methods for colon cancer by restoration of tumor suppressor genes