K-means with Empirical Mode Decomposition for Classification of Remote Sensing Image

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B. Saichandana
B.Srinivasa Rao,Dr.K.Srinivas, Visakhapatnam, India


Noise reduction is a prerequisite step prior to many information extraction attempts from remote sensed images. The noises are introduced into the images during acquisition or transmission process, affecting the classification results of the remote sensing image. In this paper, we propose to combine the K-means method with Bi-dimensional Empirical Mode Decomposition for classification of remote sensing image in order to reduce the effect of noise. We call this method as K-Means with Bi-dimensional Empirical Mode decomposition (KBEMD). We use an adaptive local weighted averaging filter in the BEMD method for removing the noise in the remote sensing image and finally K-means algorithm is used for classification of image. Using the KBEMD method on remote sensing image, we can obtain more reasonable results.


Keywords: Remote Sensing; Empirical Mode Decomposition; Image Classification, Image Processing;


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