XXII ISPRS Congress 2012: Technical Commission VII

Bibliographic data

Multivolume work

Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Document type:: Multivolume work

Volume

Persistent identifier:: 1663821976

Title:: Technical Commission VII

Scope:: 546 Seiten

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663821976

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(39,B7)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

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

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; 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:: [VII/5: METHODS FOR CHANGE DETECTION AND PROCESS MODELLING]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: ACCURACY IMPROVEMENT OF CHANGE DETECTION BASED ON COLOR ANALYSIS J. Wang, H. Koizumi, T. Kamiya

Document type:: Multivolume work

Structure type:: Chapter

G. and (CSM) rrestrial . doi eth, G., pes by posium ion and ics and 'rmany. . Upper „X. ti- Jia, L. yetation vheat at 5-357. Iyyppä, rrestrial ISPRS 6. Spatial a field. 98. 7-1000. Sheet variate e using . Field maeker, s using | ing and rrestrial ng, P., hysical support 2-281. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia ACCURACY IMPROVEMENT OF CHANGE DETECTION BASED ON COLOR ANALYSIS J. Wang, H. Koizumi, T. Kamiya System Technologies Laboratories, NEC System Technologies, Ltd, 6300212, Ikoma, Japan - (wang-jxb, koizumi-hxa, kamiya-txa)@necst.nec.co.jp Technical Commission VII/5 KEY WORDS: Change Detection, Orthoimage, Color Analysis, Illumination Change Adjustment, Location Difference Rectification ABSTRACT: Change detection is one of the most important topics in the application field of aerial images and satellite images. In this paper, a novel framework for accuracy improvement on change detection is proposed. The proposed framework consists of three parts. Firstly, the location difference between the two orthoimages for change detection is rectified globally. Secondly, the illumination change of the orthoimages from two different times is adjusted to produce the orthoimages with more unified illumination condition. Thirdly, the location difference between the two orthoimages is adjusted in more precise level of local regions. Experimental results show that the detection accuracy of change detection is greatly improved through the pre-processing of the proposed framework. 1. INTRODUCTION As one important application field of aerial images and satellite images, change detection is attracting more and more attentions in recent years. Due to the fast development of cities especially in the developing countries, there are new reconstructions, demolished old buildings, vacant land changing into grassland and so on, nearly happening everyday. This leads to dramatic land change in a short time. In order to timely update the map of these changing places in wide area, change detection with high accuracy on aerial images or satellite images is quite necessary. Before, this updating job is realized by manual check of human operators, but it turns out to take very long working time and there also exist changing regions missed by human operators. Under this background, several change detection systems have been developed to automatically carry out the change detection on aerial images and satellite images. For example, we can extract the color change and the height change based on orthoimages and Digital Surface Model(DSM), which are generated based on stereo images and aerial triangulation data. The real application projects prove that automatic change detection systems help to greatly reduce the overall processing time, and further the overall cost. At the same time, automatic systems also improve the overall detection rate, by extracting the regions apt to be missed by human operators. To assure that no changing region is missed in the final result, automatic change detection systems tend to firstly extract much larger number of candidate regions far more than the number of actually changing regions, which needs further processing by the operators to remove false detections. Though the overall processing time is already greatly reduced, operators still have to spend long time to remove wrong detections. To solve this problem, we propose a framework to reduce most of the wrong detections and at the same time keep the correct detections. The experimental results show that through the processing steps in the proposed framework, the number of wrong detections is greatly reduced and the location and range of detected regions are also improved. The rest of the paper is organized as follows. Section 2 explains the research background for the improvement of change detection. In section 3, the details of the whole methodology in three steps are stated. Experimental results are shown and analyzed in section 4. Finally, we draw a conclusion and also introduce future prospects in section 5. 2. RESEARCH BACKGROUND Due to its wide application, many change detection methods [1, 2, 3] have been proposed. In comparison, there is no systematic discussion on how to improve the accuracy of change detection by resolving some common problems in almost all change detection methods. In this paper, we concentrate on analyzing the problems that affect the accuracy of change detection. Firstly, the necessary requirements for a change detection system are discussed as follows. (1) Completeness. No changing region is missed no matter of its scale, shape and changing pattern. (2) Correctness. No unchanging regions are extracted. (3) Preciseness. The location and the range of the extracted changing regions should conform to the truth. According to these requirements, current automatic change detection systems have relatively good completeness. But to assure the completeness, some suspectable but actually unchanging regions are also detected. Through the analysis of several different projects, we find the following two main reasons for the wrongly detected regions: illumination change between two orthoimages and location difference between two datasets. At the same time, there exist incomplete candidate regions because of illumination change and location difference. We propose a new framework to solve the above two main problems, and finally find that the preciseness of the detected regions is also improved at the same time.

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