COMPARATIVE ANALYSIS THE EFFECT OF FUSION ALGORITHM ON HIGH RESOLUTION IMAGES
DOI:
https://doi.org/10.21063/jtif.2013.V1.1.1-5Keywords:
image fusion, high resolution, classification, support vector machinesAbstract
Fusi citra telah banyak diterapkan untuk berbagai keperluan salah satunya digunakan untuk penggabungan dua buah citra atau lebih baik dengan menggunakan data fusi multi sensor. Penggabungan citra fusi dilakukan dengan menyatukan citra yang mempunyai resolusi rendah (multispektral ) dengan citra spasial yang beresolusi tinggi (pankromatik). Pada penelitian ini dilakukan pengujian dan analisis citra satelit dengan menggunakan berbagai metode fusi untuk menentukan kualitas suatu citra secara visual , spekral dan akurasi klasifikasi . Teknik klasifikasi citra fusi menggunakan metode Support Vector Machines (SVMs).
Images fusion has been widely applied to imaging sensors for the purpose of resolution merge, image integration, and multi sensor data fusion. In image fusion, a low spatial resolution multispectral image is fused with a higher resolution panchromatic image to produce an image with higher spectral and spatial resolution. In this paper, we investigate the existing fusion methods based on visual ,spectral analyse and classification acuracy. The accuracy of classification result is assessed by means of the support vector machine based on radial basis function kernel. Comparing the performance of various fusion methods, it is shown that the Gram-Schmidt (GS) method yields the best accuracy, followed by the principal component analysis (PCA). The producer’s and user’s accuracies of the GS method are 91.8% and 91.1%, respectively, followed by 90.8% and 90.0% of the PCA method.
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