CN105608698B - 一种基于sae的遥感图像变化检测方法 - Google Patents
一种基于sae的遥感图像变化检测方法 Download PDFInfo
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- CN105608698B CN105608698B CN201510990465.0A CN201510990465A CN105608698B CN 105608698 B CN105608698 B CN 105608698B CN 201510990465 A CN201510990465 A CN 201510990465A CN 105608698 B CN105608698 B CN 105608698B
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- 238000000034 method Methods 0.000 title claims abstract description 25
- 238000001514 detection method Methods 0.000 claims abstract description 38
- 238000012549 training Methods 0.000 claims abstract description 29
- 238000012360 testing method Methods 0.000 claims abstract description 19
- 238000000605 extraction Methods 0.000 claims abstract description 6
- 239000013598 vector Substances 0.000 claims description 8
- 238000012937 correction Methods 0.000 claims description 6
- 238000001228 spectrum Methods 0.000 claims description 3
- 238000007670 refining Methods 0.000 claims description 2
- 230000001902 propagating effect Effects 0.000 claims 1
- 238000013528 artificial neural network Methods 0.000 abstract description 6
- 238000010586 diagram Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 3
- 239000000284 extract Substances 0.000 description 3
- 238000007477 logistic regression Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 230000011218 segmentation Effects 0.000 description 2
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- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 description 1
- 235000003140 Panax quinquefolius Nutrition 0.000 description 1
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- 235000008434 ginseng Nutrition 0.000 description 1
- 238000003709 image segmentation Methods 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10032—Satellite or aerial image; Remote sensing
- G06T2207/10044—Radar image
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Families Citing this family (17)
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CN106228130B (zh) * | 2016-07-19 | 2019-09-10 | 武汉大学 | 基于模糊自编码网络的遥感影像云检测方法 |
CN106447039A (zh) * | 2016-09-28 | 2017-02-22 | 西安交通大学 | 基于自编码神经网络的无监督特征提取方法 |
CN106780499A (zh) * | 2016-12-07 | 2017-05-31 | 电子科技大学 | 一种基于堆叠自动编码网络的多模态脑肿瘤图像分割方法 |
CN106934797B (zh) * | 2017-02-16 | 2019-09-06 | 中国测绘科学研究院 | 一种基于邻域相对熵的sar影像变化检测方法 |
CN107122733B (zh) * | 2017-04-25 | 2019-10-11 | 西安电子科技大学 | 基于nsct和sae的高光谱图像分类方法 |
CN107230201B (zh) * | 2017-05-15 | 2020-11-03 | 西安电子科技大学 | 基于样本自标定elm的在轨sar图像变化检测方法 |
CN107358261B (zh) * | 2017-07-13 | 2020-05-01 | 西安电子科技大学 | 一种基于曲线波sae的高分辨sar图像变化检测方法 |
CN109191418B (zh) * | 2018-06-22 | 2021-10-01 | 西安电子科技大学 | 一种基于收缩自编码器特征学习的遥感图像变化检测方法 |
CN109242889B (zh) * | 2018-08-27 | 2020-06-16 | 大连理工大学 | 基于上下文显著性检测与sae的sar图像变化检测方法 |
CN109558806B (zh) * | 2018-11-07 | 2021-09-14 | 北京科技大学 | 高分遥感图像变化的检测方法 |
CN109801305B (zh) * | 2019-01-17 | 2021-04-06 | 西安电子科技大学 | 基于深度胶囊网络的sar图像变化检测方法 |
CN109993727A (zh) * | 2019-03-06 | 2019-07-09 | 中国人民解放军61540部队 | 一种基于深度学习的遥感图像变化检测方法 |
CN109977968B (zh) * | 2019-03-25 | 2021-03-12 | 合肥工业大学 | 一种深度学习分类后比较的sar变化检测方法 |
CN110059658B (zh) * | 2019-04-26 | 2020-11-24 | 北京理工大学 | 一种基于三维卷积神经网络的遥感卫星影像多时相变化检测方法 |
CN111126255A (zh) * | 2019-12-23 | 2020-05-08 | 华中科技大学 | 基于深度学习回归算法的数控机床刀具磨损值预测方法 |
CN111626122B (zh) * | 2020-04-24 | 2024-01-05 | 贝壳技术有限公司 | 合成孔径雷达图像识别方法、装置、电子设备和存储介质 |
CN113256629B (zh) * | 2021-07-05 | 2022-06-24 | 之江实验室 | 一种图像标定错误检测方法及装置 |
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