An unsupervised urban change detection procedure by using luminance and saturation for multispectral remotely sensed images

Photogrammetric Engineering and Remote Sensing

Volumn 81, Issue 8, 2015, Pages 637-645

  Ye, Su ^a   Chen, Dongmei ^a  

^a QUEEN S UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE SEGMENTATION; LUMINANCE; MARKOV PROCESSES; PRINCIPAL COMPONENT ANALYSIS; REMOTE SENSING; SIGNAL DETECTION;

COMPLEMENTARY FEATURES; CONTEXTUAL INFORMATION; MARKOV RANDOM FIELDS; PRINCIPLE COMPONENT ANALYSIS; QUANTITATIVE ACCURACY; REMOTELY SENSED IMAGES; UNSUPERVISED CHANGE DETECTION; URBAN CHANGE DETECTION;

IMAGE PROCESSING;

ACCURACY ASSESSMENT; DETECTION METHOD; IMAGE ANALYSIS; LUMINESCENCE; MULTISPECTRAL IMAGE; NOISE; REMOTE SENSING; SATELLITE IMAGERY; SATURATION; SPECTRAL ANALYSIS; TECHNOLOGICAL CHANGE; THRESHOLD; UNSUPERVISED CLASSIFICATION; URBAN AREA;

EID: 84938566078     PISSN: 00991112     EISSN: None     Source Type: Journal    
DOI: 10.14358/PERS.81.8.637     Document Type: Article

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