Automated Segmentation of Urban Features from Landsat-Thematic Mapper Imagery for Use in Pseudovariant Feature Temporal Image Normalization PDF Download
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Author: Carl Salvaggio Publisher: ISBN: Category : Algorithms Languages : en Pages : 446
Book Description
"An automated segmentation algorithm for the isolation of pseudoinvariant features was developed. This algorithm utilizes rate-of-change information from the thresholding process previously associated with the pseudoinvariant feature normalization technique. This algorithm was combined with the normalization technique and applied to the six reflective bands of the Landsat Thematic Mapper for both urban and rural imagery. The segmentation algorithm and normalization technique were also applied to color infrared high resolution U2 imagery. The accuracy and precision of the normalization results were evaluated. The technique consistently produced normalization results with errors of approximately one or two reflectance units for both the rural and urban Thematic Mapper imagery as well as the visible bands of high resolution airphoto imagery. The segmentation algorithm shows great potential for the removal of human intervention in the pseudoinvariant feature temporal image normalization process."--Abstract.
Author: Carl Salvaggio Publisher: ISBN: Category : Algorithms Languages : en Pages : 446
Book Description
"An automated segmentation algorithm for the isolation of pseudoinvariant features was developed. This algorithm utilizes rate-of-change information from the thresholding process previously associated with the pseudoinvariant feature normalization technique. This algorithm was combined with the normalization technique and applied to the six reflective bands of the Landsat Thematic Mapper for both urban and rural imagery. The segmentation algorithm and normalization technique were also applied to color infrared high resolution U2 imagery. The accuracy and precision of the normalization results were evaluated. The technique consistently produced normalization results with errors of approximately one or two reflectance units for both the rural and urban Thematic Mapper imagery as well as the visible bands of high resolution airphoto imagery. The segmentation algorithm shows great potential for the removal of human intervention in the pseudoinvariant feature temporal image normalization process."--Abstract.
Author: Kevin M.. Lankheit Publisher: ISBN: Category : Cape Girardeau County (Mo.) Languages : en Pages : 142
Book Description
Compares the accuracy of pixel-based maximum likelihood and image segmentation classification techniques which were applied to the Landsat scenes of Cape Girardeau, Missouri for determining land use and land cover changes.
Author: Vladimir Mashtalir Publisher: Springer Nature ISBN: 3030354806 Category : Technology & Engineering Languages : en Pages : 279
Book Description
This book proposes a number of promising models and methods for adaptive segmentation, swarm partition, permissible segmentation, and transform properties, as well as techniques for spatio-temporal video segmentation and interpretation, online fuzzy clustering of data streams, and fuzzy systems for information retrieval. The main focus is on the spatio-temporal segmentation of visual information. Sets of meaningful and manageable image or video parts, defined by visual interest or attention to higher-level semantic issues, are often vital to the efficient and effective processing and interpretation of viewable information. Developing robust methods for spatial and temporal partition represents a key challenge in computer vision and computational intelligence as a whole. This book is intended for students and researchers in the fields of machine learning and artificial intelligence, especially those whose work involves image processing and recognition, video parsing, and content-based image/video retrieval.
Author: Robert S. Rand Publisher: ISBN: Category : Cartography Languages : en Pages : 74
Book Description
A general Change Detection (CD) methodology is investigated that involves a hybrid mix of image processing, spectral transformation, and statistical pattern recognition techniques. The Hybrid Methodology attempts to combine various forms of supporting and conflicting evidence for change into a resulting change map. The approach involves differencing registered multiband scene pairs that have undergone a spectral transformation, generating threshold masks, and applying a classifier to the masked multiband scene pairs.
Author: Yang Ou Publisher: ISBN: Category : Remote sensing Languages : en Pages : 164
Book Description
Four urban characteristics are identified through a review of current urban definitions. They are a) urban areas contain large and dense built-up areas; b) urban areas contain heterogeneous elements; c) urban areas are dominant by non-agricultural activities; and d) urban areas are distinguishable from their surrounding rural areas. Eight remote sensing image features are related to the urban characteristics, they are, the four proportions of vegetation, impervious surface, soil and water / shade, and the four textural features including angular second moment, inverse difference moment, contrast and entropy. They correspond to two types of information. Four proportional features correspond to land cover composition, and four textural features correspond to land cover configuration. The experiment results show that the combination of the eight features is valid for characterizing different kinds of areas and effective for distinguishing between urban and rural areas. The multi-resolution image segmentation algorithm is suitable for dividing a city region into homogeneous sub-regions that accord with the physical landscape. In the experiment of the algorithm with Landsat TM data, all the seven spectral bands show a decrease in the average grey-level range along a continuous region splitting process performed for all administrative regions of the study area. The average grey-level ranges in six of the seven bands are further reduced by removing the administrative boundary constraint. An urban area is successfully recognized through an iterative clustering and merging process, performed on the homogeneous regions output from the image segmentation process with the eight proportional and textual features. An experiment shows that the iterative clustering and identification is able to identify an area that can be definitely labelled as urban. Another experiment shows that the iterative merging process is able to identify the urban and rural areas of a city region with the maximum distance between them in the feature space. The resulting urban area is evaluated by a fact consistency checking. By overlapping the resulting urban area with some referenced data, it is verified that all the facts identified about the study area are satisfied by the recognition result.
Author: Carl Salvaggio
Author: Carl Salvaggio
Author: Kevin M.. Lankheit
Author: Vladimir Mashtalir
Author: Robert S. Rand
Author: Danielle Sue Taylor
Author: Yang Ou
Author: Yi-huang Tao
Author: Paul J. Samara
Author: Steven Lee Savitt
Author: Steven Earl Mathews