Proceedings, XXth congress: Proceedings, XXth congress

Altan, M. Orhan

Bibliographic data

Multivolume work

Persistent identifier:: 1663674213

Title:: Proceedings, XXth congress

Sub title:: Istanbul, 12 - 23 July 2004

Year of publication:: 2004

Place of publication:: Istanbul

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 1663674213

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist aus dem Copyrightjahr ermittelt.; Auch bezeichnet als XXth International Congress for Photogrammetry and Remote Sensing

Editor:: Altan, M. Orhan

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Document type:: Multivolume work

Volume

Persistent identifier:: 166368779X

Title:: Proceedings, XXth congress

Scope:: IV, 226 Seiten

Year of publication:: 2004

Place of publication:: Istanbul

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 166368779X

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(35,B8)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist aus dem Copyrightjahr ermittelt.

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: Altan, M. Orhan

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: A MULTI-SCALE SEGMENTATION METHOD FOR REMOTELY SENSED IMAGES BASED ON GRANULOMETRY Z. Y. Hang, X. L. Chen, Y. S. Li, C. Q. Chen

Document type:: Multivolume work

Structure type:: Chapter

A MULTI-SCALE SEGMENTATION METHOD FOR REMOTELY SENSED IMAGES BASED ON GRANULOMETRY Z. Y. Hang”, X. L. Chen”, Y.S. Li”, C. Q. Chen‘ ? State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University , 129 Luoyu Road , Wuhan, 430079, CHINA, nundini@163.com "Dept. of Civil and Structural Engineering, The Hong Kong Polytechnic University, Hong Kong, CHINA, ceysli@polyu.edu.hk LED, South China Sea Institute of Oceanography, Chinese Academy of Sciences, 164 Xingangxi Road, Guangzhou, 510301, CHINA, cqchen@scsio.ac.cn KEY WORDS: Mathematical morphology, Multi-scale segmentation, Granulometry and anti-granulometry ABSTRACT! This paper proposed a multi-scale segmentation method for remote sensing image based on mathematical morphology. In mathematical morphological operations, opening transform can extract lighter connected components and closing transform can extract darker ones with size smaller than a given structure element in a gray image. A connected component, as an object, may have a high response to a given structure element size and a lower response to others. In this paper, granulometry and anti-granulometry were used for detecting the most sensitive element structures of objects from a range of structure elements with different sizes. Granulometry, an image sequence, was obtained by a series of opening transforms to the original image by using a family of structure elements with an integral index set. Anti-granuometry was generated by closing transforms. The resulting image sequences of granulometry and unti-granuometry were then operated by a series of derivatives , and the maximum value at each pixel corresponds to the index of the most sensitive structure element. The index was taken as the morphological characteristic of the corresponding pixel. The proposed segmentation method in this paper is based on the assumption that pixels with similar morphological features belong to the same connected component. This method avoids the problems of over-segmentation and boundary pixels occurred in the classical method of morphological segmentation. & Lambert, 1999) . 1. INTRODUCTION Image segmentation is a key step in image processing and analyzing. The object expression and feature detection in an Mathematical morphology is based strictly on the mathematical image based on segmentation are required to express image in a theory, and its initial idea is to explore the structure of image by more generalized form, which make it possible to analyze and putting a structure element into it (Cui, 1999). The basic understand image in a higher level (Zhang, 2001). In general, morphological operators include erosion, dilation, opening, there are two fundamentally different strategies for image closing, which were first systematically examined by Matheron segmentation: edge detection and region growing. The standard and Serra in 1960s, and other operators can be defined by the approach to morphological segmentation is dependent on above basic operators. Mathematical morphology has been edge-detection (Pesaresi & Benediktsson, 1999), which applied successfully in many fields, such as medical imaging, segments image into different regions by the edge of structure, material sciences, and machine vision (Cui, 1999), and many but has a problem for confirming which region the boundary attempts were related to the processing of remotely sensed pixels belong to. The approach of region growing tries to cluster images, including segmentation (Pesaresi & Benediktsson, pixels with same or similar features into one region. 1999), feature extraction (Talbot, 1996; Vincent, 1998; Katartzis, et.al, 2000), road network extraction on SAR image (Chanussot The most classical segmentation method of mathematical 46

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