Multispectral image segmentation using localized spectral binarization

This paper proposes a new feature extraction method for multispectral image segmentation based in Localized Spectral Binarization (LSB). In contrast with the standard image operation, which is applied with traditional image, LSB is computed on a single pixel with numerous bands. The proposed algorithm calculates differences of spectra locally on same pixel's coordinate in different bands of the multispectral image. The difference value is converted into binary by breaking the difference values into two directions, which are the positive and negative value then the differences are thresholded to form a binary codeword. A binomial factor is assigned to these codewords to form another unique value. These values are then grouped to construct the LSB feature image where is used in the image segmentation. LANDSAT multispectral images are used in the experiment to evaluate the segmentation and classification accuracy of the proposed LSB in terms of pixel-wise image segmentation. The result shows that LSB feature outperforms the spectral feature.