Kakooei et al., 2020 - Google Patents
Shadow detection in very high resolution RGB images using a special thresholding on a new spectral–spatial indexKakooei et al., 2020
- Document ID
- 13536909646463412495
- Author
- Kakooei M
- Baleghi Y
- Publication year
- Publication venue
- Journal of Applied Remote Sensing
External Links
Snippet
Shadow detection plays an important role in remote sensing applications. Shadow should be detected with damage assessment algorithms, and it should be removed from the ground surface with semantic labeling applications. The procedure of a typical shadow detection …
- 238000001514 detection method 0 title abstract description 56
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
-
- 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
- G06T2207/20—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
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- 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
- 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
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
-
- 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
- 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
- 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
- G06K9/00442—Document analysis and understanding; Document recognition
-
- 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
- G06K9/00127—Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30244—Information retrieval; Database structures therefor; File system structures therefor in image databases
-
- 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
- G06T11/00—2D [Two Dimensional] image generation
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Li et al. | A review of building detection from very high resolution optical remote sensing images | |
Kakooei et al. | Shadow detection in very high resolution RGB images using a special thresholding on a new spectral–spatial index | |
Teodoro et al. | Comparison of performance of object-based image analysis techniques available in open source software (Spring and Orfeo Toolbox/Monteverdi) considering very high spatial resolution data | |
Chen et al. | Building detection in an urban area using lidar data and QuickBird imagery | |
Peng et al. | Object-based change detection from satellite imagery by segmentation optimization and multi-features fusion | |
Singh et al. | Cloud detection using sentinel 2 imageries: a comparison of XGBoost, RF, SVM, and CNN algorithms | |
Ghanea et al. | Automatic building extraction in dense urban areas through GeoEye multispectral imagery | |
Chen et al. | Automatic building extraction via adaptive iterative segmentation with LiDAR data and high spatial resolution imagery fusion | |
Kakooei et al. | A two-level fusion for building irregularity detection in post-disaster VHR oblique images | |
Yue et al. | Texture extraction for object-oriented classification of high spatial resolution remotely sensed images using a semivariogram | |
Huang et al. | Combined multiscale segmentation convolutional neural network for rapid damage mapping from postearthquake very high-resolution images | |
Liu et al. | Object-oriented detection of building shadow in TripleSat-2 remote sensing imagery | |
Abujayyab et al. | Integrating object-based and pixel-based segmentation for building footprint extraction from satellite images | |
Zhao et al. | Road damage detection from post-disaster high-resolution remote sensing images based on tld framework | |
Azevedo et al. | Shadow detection using object area-based and morphological filtering for very high-resolution satellite imagery of urban areas | |
Srivastava et al. | Investigations on extraction of buildings from RS imagery using deep learning models | |
Yeom et al. | Detecting damaged building parts in earthquake-damaged areas using differential seeded region growing | |
Byun et al. | Relative radiometric normalization of bitemporal very high-resolution satellite images for flood change detection | |
Cao et al. | Automatic change detection in remote sensing images using level set method with neighborhood constraints | |
Sebastian et al. | Significant full reference image segmentation evaluation: a survey in remote sensing field | |
Zong et al. | Building change detection from remotely sensed images based on spatial domain analysis and Markov random field | |
Ghaffarian et al. | Automatic vehicle detection based on automatic histogram-based fuzzy C-means algorithm and perceptual grouping using very high-resolution aerial imagery and road vector data | |
Abraham et al. | Analysis of satellite images for the extraction of structural features | |
Kakooei et al. | VHR semantic labeling by random forest classification and fusion of spectral and spatial features on Google Earth Engine | |
Bhaskaran et al. | Rule-based classification of high-resolution imagery over urban areas in New York City |