Identifiability of parametric models
Identifiability of parametric models
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Computer Vision and Image Understanding
Discrete Markov image modeling and inference on the quadtree
IEEE Transactions on Image Processing
Decomposition and Classification of Spectral Lines in Astronomical Radio Data Cubes
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
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A new method for the multiband segmentation of a spectroscopic line data cube is presented. This method is intended to help astronomers to handle complex spectroscopic line data cubes where the inspection of the channel and moment maps is difficult. Due to the Hughes phenomenon, the number of input images for the segmentation process is limited. Therefore, the spectrum of each pixel is fitted with a mixture of 6 Gaussians with fixed mean values and variances. The maps of the Gaussian weights are the input for a Markovian segmentation algorithm. The final segmentation map contains classes of pixels with similar spectral line profiles. The application of our method to the HI data cube of the Virgo spiral galaxy NGC 4254 shows that kinematically interesting regions can be detected and masked by our method.