Ali Cam

Combined Efficiency of RPC and DEM Accuracy on Georeferencing Accuracy of Orthoimage: Case Study With Pléiades Panchromatic Mono Image

Generation of orthoimages in remote sensing and photogrammetry is a common and sometimes mandatory issue. The desired georeferencing accuracy of the orthoimage depends on two main factors: accuracy of transformation parameters and density and accuracy of height information. The objective of this letter is to estimate the combined efficiency of accuracies of refined rational polynomial coefficients and digital elevation models on georeferencing accuracy of the orthoimage utilizing the figure condition method (FCM). In this letter, details of the method, the characteristics of the evaluated Pléiades panchromatic mono image and auxiliary data, and also the test site are presented. The findings were compared with other results from high-resolution satellite images such as those from IKONOS, QuickBird, and OrbView-3. It is observed that the FCM might be preferred to estimate the overall georeferencing accuracy of an orthoimage, reaching ± 0.3-2.7-pixel accuracy range. The Pléiades panchromatic mono image presents almost equal accuracy as the compared images. The research was carried out on the Zonguldak (Turkey) test site which has mountainous and extremely undulating topography.

Pan-sharpening quality investigation of PLÉIADES-1A images

Abstract Optical remote sensing satellites obtain MS and Pan images simultaneously over the same coverage area. Remote sensing and image processing communities are working on different pan-sharpening methods capable of taking advantage of MS and Pan images. Each remote sensing system has its own advantages and disadvantages, leading to the question ‘Which pan-sharpening method should be used for which type of imagery?’ The aim of this research is to investigate the pan-sharpening performance of PLÉIADES-1A images. For this purpose, pan-sharpened images were generated using PCA, IHS and Brovey Transform which are the most popular pan-sharpening methods. Then, the pan-sharpened images were evaluated quantitatively using Correlation Coefficient, Root Mean Square Error, Relative Average Spectral Error, Spectral Angle Mapper and Erreur Relative Globale Adimensionnelle de Synthése. In addition, pan-sharpened images were evaluated qualitatively by taking object availability and completeness into consideration.

RASAT ve GÖKTÜRK-2 Görüntülerinin Gerçek Yer Örnekleme Aralığının Belirlenmesi

Optik uydu goruntulerinin sundugu konuma bagli bilgi icerigini etkileyen en onemli etkenlerden birisi radyometrik cozunurluktur. Farkli algilayicilarla elde edilen goruntuler ayni geometrik ve spektral cozunurluge sahip olsalar bile eger radyometrik cozunurlukleri farkli ise bu goruntulerden elde edilecek bilginin niteligi farklilik gosterecektir. Hatta ayni radyometrik cozunurluge sahip olsalar dahi, bazen goruntuler geometrik cozunurlugu arttirilarak (yani yer ornekleme araligi kucultulerek) kullaniciya sunulmaktadir. Bu durumda goruntunun gercek yer ornekleme araliginin belirlenmesi uygun olacaktir. Gercek yer ornekleme araliginin belirlenebilmesi icin Matlab ortaminda epix adi verilen bir yazilim gelistirilmistir. Yazilim, goruntulerdeki duzgun bina kenarlarinin golgeleri ile cati dokusu arasindaki gri deger gecislerinin ortalamasini alarak, aralarindaki farklari belirler ve boylece kenar yayilim fonksiyonu ilkesine bagli olarak goruntulerin gercek yer ornekleme araligini hesaplar. epix yazilimi goruntu uzerinden kenar belirleme islemini Canny operatoru yardimi ile gerceklestirmektedir. Orijinal goruntu ve Canny operatoru araciligi ile uretilen kenarlar cakistirilarak kullanicinin daha kolay kenar belirlemesi saglanmistir. Uygulama, RASAT ve GOKTURK-2 uydu goruntuleri ile gerceklestirilmistir. Yapilan arastirmada goruntulerin gercek geometrik cozunurlugu yaklasik olarak 1 piksel olarak bulunmustur. Dolayisiyla bu goruntuler normal yer ornekleme araligi ile kullanilabilmektedir.

Position accuracy assessment of Göktürk-2 satellite images by using Rational Function Model

Examination of geographical position accuracy of Göktürk-2 satellite images by using RFM (Rational Function Model) is the main objective of this work. In order to work in condition of no altitude data, polynomial model has been preferred. Translation model between image coordinates and geographical coordinates has been developed and position accuracy of the model has compared with Göktürk-2 Level 2 image processing level product. According to test of the models with collected GCPs (Ground Control Point), we had calculated 4.83 pixel RMS (Root Mean Square) error in line, 8.51 pixel RMS error in column; model generated by satellite parameters has given us 8.93 pixel RMS (Root Mean Square) error in line, 13.88 pixel RMS error in column.