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You searched for: Journal International journal of remote sensing Remove constraint Journal: International journal of remote sensing Publication Year 2019 Remove constraint Publication Year: 2019 Source 2019 v.40 no.9 Remove constraint Source: 2019 v.40 no.9 Subject algorithms Remove constraint Subject: algorithms
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1. A coupling translation network for change detection in heterogeneous images

Author:
Gong, Maoguo; Niu, Xudong; Zhan, Tao; Zhang, Mingyang
Source:
International journal of remote sensing 2019 v.40 no.9 pp. 3647-3672
ISSN:
1366-5901
Subject:
algorithms; data collection; remote sensing
Abstract:
... Based on the images acquired through different sensors, change detection is much more challenging than those based on homogeneous images. The main reason behind it is that the heterogeneous image-pair cannot be directly compared in original observation space due to their distinct statistical properties. In order to detect the changes, we establish a coupling variational autoencoder (VAE) to transf ...
DOI:
10.1080/01431161.2018.1547934

2. A high fidelity haze removal algorithm for optical satellite images using progressive transmission estimation based on the dark channel prior

Author:
Huang, Wei; Wang, Yueyun; Wang, Rui
Source:
International journal of remote sensing 2019 v.40 no.9 pp. 3486-3503
ISSN:
1366-5901
Subject:
accuracy; algorithms; image analysis; remote sensing
Abstract:
... In this paper, a high fidelity haze removal algorithm is proposed for optical satellite images by using progressive transmission estimation based on the dark channel prior (DCP). The transmission is estimated adaptively according to the histogram of the dark channel image and the constraint of maximum transmission. Then, the guided filter is used to refine the transmission to obtain a continuous t ...
DOI:
10.1080/01431161.2018.1547451

3. Densely connected deep random forest for hyperspectral imagery classification

Author:
Cao, Xianghai; Li, Renjie; Ge, Yiming; Wu, Bin; Jiao, Licheng
Source:
International journal of remote sensing 2019 v.40 no.9 pp. 3606-3622
ISSN:
1366-5901
Subject:
algorithms; hyperspectral imagery; models; remote sensing
Abstract:
... In very recent years, deep learning based methods have been widely introduced for the classification of hyperspectral images (HSI). However, these deep models need lots of training samples to tune abundant parameters which induce a heavy computation burden. Therefore, most of these algorithms need to be accelerated with high-performance graphics processing units (GPU). In this paper, a new deep mo ...
DOI:
10.1080/01431161.2018.1547932

4. Registrating large mismatching SAR images based on corners and surface extremum strategy

Author:
Yao, Guobiao; Zhang, Li; Shi, Tongguang; Deng, Kazhong
Source:
International journal of remote sensing 2019 v.40 no.9 pp. 3555-3570
ISSN:
1366-5901
Subject:
algorithms; geometry; remote sensing; synthetic aperture radar
Abstract:
... Robust and accurate registration remains a difficult task for large mismatching Synthetic Aperture Radar (SAR) images because of severe viewpoint distortion, repetitive patterns, and speckle noise. In this paper, we propose a coarse-to-fine registration method with high precision by integrating corners and Surface Extremum Strategy (SES). Our method involves three steps. First, initial correspondi ...
DOI:
10.1080/01431161.2018.1547930

5. Satellite-based analysis of regional evapotranspiration trends in a semi-arid area

Author:
Jin, Xiaomei; Zhu, Xiaoqian; Xue, Yang
Source:
International journal of remote sensing 2019 v.40 no.9 pp. 3267-3288
ISSN:
1366-5901
Subject:
agricultural land; algorithms; cropping systems; energy balance; environmental factors; evapotranspiration; land cover; normalized difference vegetation index; remote sensing; satellites; semiarid zones; shrubs; time series analysis; urban areas; vegetation; water budget; water management; wetlands; China; Yellow River
Abstract:
... A regional framework for a spatial and temporal distributed assessment of time series trends in the hydrological variable and its related ecological factors of an arid area was presented in this research. To achieve this, we tested the Surface Energy Balance System (SEBS) algorithm for estimating evapotranspiration (ET) in regional scale and the result was further validated by water budget. The ET ...
DOI:
10.1080/01431161.2018.1500727

6. SRAD-CNN for adaptive synthetic aperture radar image classification

Author:
Anjun, Zhang; Yang, Xuezhi; Jia, Lu; Ai, Jiaqiu; Xia, Jingfan
Source:
International journal of remote sensing 2019 v.40 no.9 pp. 3461-3485
ISSN:
1366-5901
Subject:
algorithms; anisotropy; immunity; remote sensing; synthetic aperture radar
Abstract:
... The performance of synthetic aperture radar (SAR) image classification based on a conventional convolutional neural network (CNN) is limited by a trade-off between immunity to speckle noise and the ability to locate boundaries accurately. Difficulties regarding the accurate location of boundaries are a result of the smoothing effect of the pooling layer. To address this issue, we propose a novel f ...
DOI:
10.1080/01431161.2018.1547450

7. Unsupervised hyperspectral feature selection based on fuzzy c-means and grey wolf optimizer

Author:
Xie, Fuding; Lei, Cunkuan; Li, Fangfei; Huang, Dan; Yang, Jun
Source:
International journal of remote sensing 2019 v.40 no.9 pp. 3344-3367
ISSN:
1366-5901
Subject:
Aesculus; algorithms; data collection; hyperspectral imagery; remote sensing; selection methods; wolves
Abstract:
... Hyperspectral image (HSI) with hundreds of narrow and consecutive spectral bands provides substantial information to discriminate various land-covers. However, the existence of redundant features/bands not only gives rise to increasing of computation time but also interferes the classification result of hyperspectral images. Obviously, it is a very challenging problem how to select an effective fe ...
DOI:
10.1080/01431161.2018.1541366