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A new noise removal algorithm based on improved neural network, is applied to remove the impulse noise of the digital images. First of all, an improved neural network is used to detect the noise-pixels and distinguish it from noise-free pixels efficiently; Second, the noise-pixels are replaced further by the suitable pixel which has the most local similarity; Finally, the output is the combination...
A new impulse noise removal technique which is based on wavelet neural network, is applied to restore digital images corrupted by impulse noise. First, wavelet neural network is used to detect the noise-pixels and distinguish it from noise-free pixels; Second, the noise-pixels are classified further by corresponding threshold and assigned the coefficient; Finally, the median filter is combined with...
In this paper, an improved neural network is applied to CCD noise removal in digital image. According to the characteristics of the nonlinear response function in the CCD camera, the denoising scheme is based on the adaptive window sizes and parameter of the filter. The improved NN both approaches to CCD PTC (photon transfer curve) and classifies it in nonlinearity and assigns the optimum coefficient...
Identifying and predicting the situation of traffic flow play an important role in traveler information broadcast and real-time traffic control. In this paper, a short-term traffic flow prediction model based on the parallel self-scaling quasi-Newton (SSPQN) neural network is presented. In this method, a set of parallel search directions are generated at the beginning of each iteration. Each of these...
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