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:: VISUAL AND STATISTICAL QUALITY ASSESSMENT AND IMPROVEMENT OF REMOTELY SENSED IMAGES S. Mohammad Shahrokhy

Document type:: Multivolume work

Structure type:: Chapter

VISUAL AND STATISTICAL QUALITY ASSESSMENT AND IMPROVEMENT OF REMOTELY SENSED IMAGES S.Mohammad Shahrokhy Iran's Space Agency- Tehran — Iran s m sh(ghotmail.com KEYWORDS: Atmospheric, Radiometric, Geometric, QualityDiagnosis, Assessment, Improvement Elimination ABSTRACT: Remotely sensed images are interpreted pixel by pixel, using spectral vector analysis methods. Most kind of noise and perturbation in pixel value or position cause misinterpretation. In this paper most common Radiometric, Atmospheric and Geometric defects of remotely sensed images are investigated along with the diagnosis and elimination methods on some high and medium resolution satellite images. Quality assessment isperformed in both visual and statistical manner and also qualitymprovement is fulfilled in both Manual and Automatic ways. Many technical methodsare used such as histogram transformation, mean, variance and median calculation of lines and bands, spatial filtering, template matchingyectifications using GCPs and brghtness temperature and reflectance checking. Visual diagnosis of defects isoften more precise but not appropriate for automatic procedures. Manual elimination of the defects is also more accurate however time consuming and user dependent. 1. INTRODUCTION ; : ; bass ; uality Defect Visual Diagnosis Statistical Reliable interpretation and results necessitateinput data Quality Q y > Diagnosis Assessment (QA) and sometimes Quality Improvement (QD). Striping Different overall Significandy On the other hand, in automatic procedures, image Quality should be checked to accept or reject the input or sometimes improve itto be able to cope with the expectedduty. Remote sensing image Quality generally has three aspects Radiometric Quality, Atmospheric Quality and Geometric Quality. Radiometric Quality is affected by sensor Le eo . S c € right € SITIC characteristics and detector responses. Striping Drop lines, Noise Dark amd bright Radiometric . n EM eL 3 es points at the anomalies Noise and Band missing are of this sort. AtmosphericQuality is ; ; ] ; background dependent on the circumstances at the imaging time. Cloud T = 7 = as ; n° he Band Missing Lack of data in a Zero variance of a cover and Haze are of this type. Geometric Quality is either band Band at an dependent on sensor characteristics and also satellite sitation such as attitude, position, velocity and perturbations. Earth} surface relief is another important factoraffecting Geometric Quality of the image. Band to band Misregistration and image to map Misregistration areof geometric Quality elements (QE) [t is essential to note that each sensor has special Quality Assessment and Quality Improvement methods, thresholds and coefficients So images of each sensor must be processed separately. In this research, TERRA-MODIS, NOAA-AVHRR, IRS-PAN and IRS-LISS III images are investigated. Many works have been done on image Quality control (Barrett 1990, Nill & Bouzas 1992, Eskicioglu & Fisher 1995, Barrett 1995, Westen et al 1995, Taylor 1998, Avicibasand Sankur 2000) and generally each company provides a compbte report of its sensor imags and products Quality e.g. EOS (Chu et al 2000 , Vermote et al 1997). 2. QE AND DEFECT DIAGNOSIS 2.1 Radiometric Quality Assessment Radiometric Quality elements and recognition methods are briefly listedin Table 1. 104 brightness of adjacent lines different variance and mean of adjacent lines Drop Line Null scan line Zero variance of a line Table 1. Radiometric Qualitydefects and diagnosis methods Striping is caused by different response of elements of a detector array to same amount of inoming EM energy. This phenomenon causes heterogeneity in overall brightness of adjacent lines figure 1). b hd Figure I. Image No.l (MODIS) with stripes in à

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