RASAT verisi kullanarak farklı pan-keskinleş rme yöntemlerinin ista s ksel analizi

RASAT uydusu tasarımı ve üre mi Türkiye de gerçekleş rilmiş olan ilk yerli yer gözlem uydusudur. Güneş ile eş zamanlı gö- rüngede bulunan RASAT 7.5 m ve 15 m mekansal çözünürlükte pankroma k ve mul spektral görüntü sağlamaktadır. Uyduya ait teknik bilgiler Tablo 1'de sunulmuştur (Erdoğan vd., 2016)

Sta s cal analysis of different pan-sharpening methods using RASAT data

The research evaluates the image fusion techniques using RASAT image which is one of the op cal re- mote sensing satellites launched by the Republic of Turkey. The data has 7.5 m ground resolu on panch- roma c and 15 m mul spectral bands (red, green and blue). The aim of the study is to compare the images fusion methods to achieve spa ally improved and spectrally preserved higher resolu on RASAT data. The performance of the data was inves gated by different image fusion methods. For this pur- pose, Ehlers fusion, High Pass Filtering (HPF), Intensity Hue Satura on (IHS) and Principal Component Analysis (PCA) data fusion methods were applied and inves gated. The study area is located in Mene- men Izmir province, west of Turkey. The area has different land use classes such as cul vated Şelds, bareland, wetland, water body and pasture. Qualita ve and quan ta ve analyses were applied to as- sess the performance of the fused images. Lower resolu on mul spectral data was compared to fused images visually and color distor ons were inves gated. For the quan ta ve analysis different sta s cal metrics were u lized. In this frame, Correla on Coefficient (CC), Universal Image Quality Index (UIQI), Root Mean Square Devia on (RMSE) and Rela ve Dimensionless Global Error in Synthesis-Erreur Re- la ve Globale Adimensionnelle de Synthese (ERGAS) were performed for quality assessments of spa- ally improved data. Regarding to the results of the pan-sharpening methods it is concluded that Ehlers preserved the best color informa on while the result of HPF provided higher sta s cal results

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