Nothing Special   »   [go: up one dir, main page]

Cai et al., 2010 - Google Patents

Feature-driven multilayer visualization for remotely sensed hyperspectral imagery

Cai et al., 2010

Document ID
14938536480719547841
Author
Cai S
Du Q
Moorhead R
Publication year
Publication venue
IEEE Transactions on Geoscience and Remote Sensing

External Links

Snippet

Displaying the abundant information contained in a remotely sensed hyperspectral image is a challenging problem. Currently, no approach can satisfactorily render the desired information at arbitrary levels of detail. In this paper, we present a feature-driven multilayer …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • G06T11/20—Drawing from basic elements, e.g. lines or circles
    • G06T11/206—Drawing of charts or graphs
    • 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
    • G06K9/00657—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas of vegetation
    • 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
    • G06K9/36—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
    • G06K9/4652—Extraction of features or characteristics of the image related to colour
    • 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
    • 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
    • G06T2207/20—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
    • G06K9/20—Image acquisition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • G06T11/001—Texturing; Colouring; Generation of texture or colour
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements

Similar Documents

Publication Publication Date Title
Man et al. Pixel-and feature-level fusion of hyperspectral and lidar data for urban land-use classification
Gerber et al. Predicting missing values in spatio-temporal remote sensing data
Liu et al. Multiscale morphological compressed change vector analysis for unsupervised multiple change detection
Kinkeldey et al. How to assess visual communication of uncertainty? A systematic review of geospatial uncertainty visualisation user studies
Small A global analysis of urban reflectance
Petropoulos et al. Spectral angle mapper and object-based classification combined with hyperspectral remote sensing imagery for obtaining land use/cover mapping in a Mediterranean region
S Bhagat Use of remote sensing techniques for robust digital change detection of land: A review
Zhang et al. Evaluation of Goddard’s LiDAR, hyperspectral, and thermal data products for mapping urban land-cover types
Iordache et al. A dynamic unmixing framework for plant production system monitoring
Chen et al. Spectral unmixing using a sparse multiple-endmember spectral mixture model
Qin et al. Weakly supervised adversarial learning via latent space for hyperspectral target detection
Cai et al. Hyperspectral imagery visualization using double layers
Yang et al. A fuzzy-statistics-based principal component analysis (FS-PCA) method for multispectral image enhancement and display
Ivits et al. Landscape structure assessment with image grey‐values and object‐based classification at three spatial resolutions
Camacho et al. An analysis of spectral variability in hyperspectral imagery: a case study of stressed oil palm detection in Colombia
Malik et al. Computer vision models for comparing spatial patterns: understanding spatial scale
Saralioglu et al. Use of crowdsourcing in evaluating post-classification accuracy
Cai et al. Feature-driven multilayer visualization for remotely sensed hyperspectral imagery
Peacock et al. Accuracy assessment of supervised and unsupervised classification using Landsat imagery of Little Rock, Arkansas
Requena-Mesa et al. Predicting landscapes from environmental conditions using generative networks
Acito et al. CWV-Net: A deep neural network for atmospheric column water vapor retrieval from hyperspectral VNIR data
Lin et al. An investigation on worst‐case spectral reconstruction from RGB images via Radiance Mondrian World assumption
Li et al. A comparative study on intra-annual classification of invasive saltcedar with Landsat 8 and Landsat 9
Gong et al. Using UAV LiDAR Intensity Frequency and Hyperspectral Features to Improve the Accuracy of Urban Tree Species Classification
Wolfe et al. Hyperspectral analytics in envi target detection and spectral mapping methods