Polyacrylonitrile fibers were treated with a nitrogen glow-discharge plasma. The surfaces of untreated and treated fibers were examined with contact angle measurements, atomic force microscopy (AFM) and X-ray photoelectron spectroscopy (XPS). Surface energy calculations of the fibers were carried out from contact angle measurements using the relationships developed by Fowkes. It is found that plasma treatment causes a reduction in water contact angle on the fiber surfaces. The dispersion component of surface energy changes slightly, while the polar component is increased significantly from 14.6 mN/m to 58.7 mN/m and the total surface energy increase is 139%. The increase of surface energy is mainly caused by the introduction of hydrophilic groups on the fiber surfaces after plasma treatment.
Feature extraction and image classification using PolSAR images is currently of great interest in SAR applications. On the basis of the sparse characteristics of the features for PolSAR image classification, a supervised PolSAR image classification method based on sparse representation is proposed in this paper, in which the test data can be firstly projected onto a subset of training vectors from the dictionary, then the residual errors with respect to each atom are evaluated and considered as the criteria for classification, and the ultimate class results can be obtained according to the atom with the least residual error. In addition, a Simplified Matching Pursuit (SMP) algorithm is proposed to solve the optimization problem of sparse representation of PolSAR images. The experimental results of Danish EMISAR L-band fully polarimetric SAR data of Foulum Area (DK) confirm our method outputs an excellent result and moreover the classification process is simpler and less time consuming.
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