2-D orthogonal lattice filter based image segmentation

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 (2D) 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