Based on multistage theory and NSCT, a new feature-based image watermarking scheme is proposed in this paper. Firstly, the multistage Harris detector is utilized to extract steady feature points from the host image; then, the local feature regions (LFR) are ascertained adaptively according to the feature scale theory, and they are scaled to a standard size; finally, the digital watermark are embedded into no subsample contour let low frequency area, in the low frequency regions made pseudo-Zernike moment calculation. Experimental results show that the proposed scheme is not only invisible and robust against common signals processing such as median filtering, sharpening, noise adding and JPEG compression et al, but also robust against the unclassified geometric attacks such as rotation, translation, scaling, row or column removal, shearing, local geometric distortion and combination attacks et al.
Abstract:The high altitude meteorological parameters include longitude, latitude, atmospheric pressure, temperature, humidity, etc., which are influenced between each parameter, therefore, it is very important to deal with and analyze these parameters. In this paper, we employ MATLAB software, research the basic algorithm of BP neural network, compare resilient BP algorithm, the Fletcher-Reeves algorithm and the proportion conjugate gradient algorithm, establish the forecast model of high altitude meteorological data with Fletcher-Reeves algorithm, and analyze the influence of the hidden layer nodes of training. Finally, we analyze the errors of the sensor models, obtain the optimal results using neural network, and ascertain the final data processing method.
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