Bu et al., 2020 - Google Patents
Mask-CDNet: A mask based pixel change detection networkBu et al., 2020
- Document ID
- 14072774851395479812
- Author
- Bu S
- Li Q
- Han P
- Leng P
- Li K
- Publication year
- Publication venue
- Neurocomputing
External Links
Snippet
Change detection between multi-temporal images becomes a core technique widely used in various fields. But there still exist some challenging issues in the field of change detection. This thesis mainly focuses on the issue that two compared images captured at different times …
- 238000001514 detection method 0 title abstract description 105
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
- G06K9/4604—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections
- G06K9/4609—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections by matching or filtering
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/20—Image acquisition
- G06K9/32—Aligning or centering of the image pick-up or image-field
- G06K9/3233—Determination of region of interest
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20112—Image segmentation details
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6201—Matching; Proximity measures
- G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/0063—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K2209/00—Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2200/00—Indexing scheme for image data processing or generation, in general
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Ye et al. | A robust multimodal remote sensing image registration method and system using steerable filters with first-and second-order gradients | |
Li et al. | Accurate cloud detection in high-resolution remote sensing imagery by weakly supervised deep learning | |
Liu et al. | AFNet: Adaptive fusion network for remote sensing image semantic segmentation | |
Bu et al. | Mask-CDNet: A mask based pixel change detection network | |
Wan et al. | An object-based hierarchical compound classification method for change detection in heterogeneous optical and SAR images | |
Zheng et al. | Unsupervised saliency-guided SAR image change detection | |
Kang et al. | Extended random walker for shadow detection in very high resolution remote sensing images | |
Lu et al. | GAMSNet: Globally aware road detection network with multi-scale residual learning | |
Cao et al. | Vehicle detection from highway satellite images via transfer learning | |
Ma et al. | Fast SAR image segmentation with deep task-specific superpixel sampling and soft graph convolution | |
Han et al. | Aerial image change detection using dual regions of interest networks | |
Chen et al. | 2D and 3D object detection algorithms from images: A Survey | |
Cho et al. | Deep monocular depth estimation leveraging a large-scale outdoor stereo dataset | |
Yan et al. | Multimodal image registration using histogram of oriented gradient distance and data-driven grey wolf optimizer | |
Lu et al. | Cross-domain road detection based on global-local adversarial learning framework from very high resolution satellite imagery | |
Zhu et al. | Robust registration of aerial images and LiDAR data using spatial constraints and Gabor structural features | |
Jiang et al. | Intelligent image semantic segmentation: a review through deep learning techniques for remote sensing image analysis | |
Wang et al. | The poor generalization of deep convolutional networks to aerial imagery from new geographic locations: an empirical study with solar array detection | |
Li et al. | Progressive fusion learning: A multimodal joint segmentation framework for building extraction from optical and SAR images | |
Wang et al. | Urban building extraction from high-resolution remote sensing imagery based on multi-scale recurrent conditional generative adversarial network | |
EP3553700A2 (en) | Remote determination of containers in geographical region | |
Song et al. | An easy-to-hard learning strategy for within-image co-saliency detection | |
Li et al. | 3DCentripetalNet: Building height retrieval from monocular remote sensing imagery | |
Zhang et al. | Optical and SAR image dense registration using a robust deep optical flow framework | |
Huang et al. | Change detection with absolute difference of multiscale deep features |