FUZZY BASED GRAPH CUT CLASSIFICATION OF HYPER-SPECTRAL IMAGE

Author(s):

Kavitha Devi.K , Christian college of Engg & Tech. Oddanchatram; Kamatchi.P, Christian college of Engg & Tech. Oddanchatram; Shanmugapriya,M, Christian college of Engg & Tech. Oddanchatram; Sujatha.V, Christian college of Engg & Tech. Oddanchatram; Sugapriya.K, Christian college of Engg & Tech. Oddanchatram

Keywords:

Hyper-Spectral Image, AIN, LASSO

Abstract:

Image segmentation is an important image processing technique which is used to analyze what is inside the image. Image segmentation is used to separate an image into several “meaningful” parts. It is an old research, there is still no robust solution toward it. There are two main reasons, the first is that the content variety of images is too large, and the second one is that there is no benchmark standard to judge the performance. In this project we develop to segment the image in a better way in this project we use to get a better segmented Image. Here we used this graph cut technique to solve the image segmentation problem. And we got successful results in partitioning an in image. In this method we use an efficient computational technique based on the eigenvalues and eigenvectors to get an optimized segmented Image. We have applied this approach to segment the static images.

Other Details:

Manuscript Id	:	IJSTEV2I10073
Published in	:	Volume : 2, Issue : 10
Publication Date	:	01/05/2016
Page(s)	:	321-326

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