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Segmentation Algorithm for Road in High Resolution Remote Sensing Images

Author: MaWen
Tutor: ZhouShaoGuang
School: Hohai University
Course: Photogrammetry and Remote Sensing
Keywords: Image Segmentation High Resolution Image Maximum internal variance between Grayscale Consistency General characteristics
CLC: TP391.41
Type: Master's thesis
Year: 2006
Downloads: 508
Quote: 15
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Abstract


Since the SPOT-5, IKONOS, QuickBird and other satellite was successfully launched and put into commercial operation since remote sensing applications into a new era , correspondingly, high-resolution remote sensing image processing and information extraction put forward new demands. Automatic extraction from remote sensing images Photogrammetry and Remote Sensing road problem areas and priorities , it is for Photogrammetry and Remote Sensing automated image analysis plays a crucial role. Image Segmentation realized through road image binarization , and then extract the binary image on the road is a representative research directions. The main content of this paper is the way the image segmentation algorithm . High-resolution remote sensing images for urban road section typical of the specific characteristics of remote sensing images using the corresponding algorithm will split up the road segment , the final extract provided for road ready . Thesis as follows: ( a ) a detailed analysis of some of the existing theories and methods based on specific high-resolution remote sensing image segmentation technology, and summarizes the advantages and disadvantages of each method ; ( 2 ) a detailed study based on the maximum variance between inside France 's multi-class image segmentation algorithm , summed up the road which was used directly image segmentation limitations ; ( 3 ) proposed two new suitable for urban high-resolution remote sensing image segmentation method - based on local gray road consistency image segmentation method based on integrated features of image segmentation. Based on the consistency of local gray road image segmentation method considered gray information and spatial information combined with the image segmentation, segmentation experimental results show that this method is better, to complex high-resolution remote sensing images quickly split . Based on an integrated feature of image segmentation method combines the grayscale image and texture features for image segmentation fuzzy clustering road to overcome the original features using a single segmentation defects.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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