2D orthogonal lattice filter based image segmentation


AYKUT S., GURCAN R., Erer I.

IEEE International Geoscience and Remote Sensing Symposium, Alaska, United States Of America, 20 - 24 September 2004, pp.3814-3817 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Alaska
  • Country: United States Of America
  • Page Numbers: pp.3814-3817

Abstract

The purpose of image segmentation is to partition an image into homogeneous regions. Features are of major importance in image segmentation. In this work, a new method is proposed in which features used for segmentation are reflection coefficients of the two-dimensional(2-D) orthogonal lattice filters. Principal Component Analysis (PCA) is applied to the features for reducing the complexity of the work. A minimum distance classifier is used in the classification algorithms. The proposed method is compared with the discrete wavelet transform which is a common segmentation algorithm. In our work, selected image is a monospectral optical image.