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A new algorithm for lossless compression of hyperspectral imagery is proposed. First, the average value of four neighbour pixels of the current pixel is calculated as local mean, which is subtracted by the current pixel to eliminate correlation in the current band image. The residual produced by this step is called local difference. The local differences of the pixels which co-locate with the current pixel in previous bands form the input vector of the recursive least square (RLS) filter, by which the prediction value of the current local difference is produced. Then, the prediction residual is sent to the adaptive arithmetic encoder. Experiment results show that the proposed algorithm produces state-of-the-art performance with relatively low complexity, and it is suitable for real-time compression on satellites.
Mobile mapping systems that detect and geo-reference road markings almost always consist of a stereo camera system integrated with a global positioning system/inertial navigation system. The data acquired by this navigational system allows features detected in the stereo images to be assigned global co-ordinates. An essential step in this process is the calibration of the cameras, as it relates the pose of the two cameras to each other and a world co-ordinate system. In Europe, road markings must be evaluated from a 35 m range, so the cameras are required to have a wide field of view. Traditional calibration methods supposedly require a calibration object that would fill most of the calibration images. This large field of view would require a calibration object of substantial size that would be impractical for the purposes of this portable system. This study explores the theory of camera calibration and then details two camera calibration techniques (using portable 3D and 2D calibration objects). The accuracy of these methods is then evaluated using a ground-truth experiment.
Based on the polarimetric-basis transformation principle, a method for utilisation of the scattering mechanism vectors for land classification is proposed. The experimental results show that both the amplitude and the phase components of the vectors can be used for land classification. By implementing different linear transformation processes of the scattering matrix, a variety of areas can be extracted separately.
