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In order to improve image denoising effect, an exponential threshold function de-noising method is proposed, which can overcome the continuity problem of the hard-threshold function, and eliminate the constant deviation problem of the soft threshold function by constructing a new threshold function with arbitrary derivable. Experimental results showed that the new threshold function could obtain higher...
For a variety of interference exists in the collected real-time traffic images at the scene, and affects the traffic images of authenticity, we de-noise the traffic images with wavelet threshold. In order to verify the effect of de-noising, we add noise to the images, and then de-noise them in the method by hard threshold. The simulation experiments show that the de-noising effect is obvious and can...
This paper achieves optimal 3D point cloud reconstruction based on the specific experiment and concrete actions, and the reconstruction results realistically reflect the real object. We introduce a pipeline for surface reconstruction, including K-nearest neighbor method for point cloud data de-noising, Poisson-disk sampling to simplify the point cloud data, k-nearest neighbor method for normal estimation...
B-splines caught interest of many engineering applications due to their merits of being flexible and provide a large degree of differentiability and cost/quality trade off relationship. However they have less impact with continuous time applications as they are constructed from piecewise polynomials. On the other hand, Exponential spline polynomials (E-splines) represent the best smooth transition...
Weighted Fuzzy C-Mean clustering algorithm by one-dimensional histogram can classify accurately pixels of coal flotation froth images into three kinds such as bubble vertex, the bubble surface and the background to increase the contrast of bubble edge and background, accurately positioning the bubble region for its fast convergence speed, real-time characteristics. After de-noised based on morphological...
Independent component analysis (ICA) is a statistical technique where the goal is to represent a set of random variables as a linear transformation of statistically independent component variables. This paper proposes a new extended model for CT medical image de-noising, which is using independent component analysis and dynamic fuzzy theory. Firstly, a random matrix was produce to separate the CT...
Image de-noising and enhancement form two fundamental problems in many engineering and biomedical applications. The paper is devoted to the study of the multi-resolution approach to this topic employing the Haar wavelet transform and its application to processing of volumetric magnetic resonance image sets corrupted with additional noise. The resulting coefficients are thresholded and exploited for...
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