3 results about "Mellin transform" patented technology

The invention discloses a single-input single-output channel data analysis and model construction method oriented to an urban environment. In order to improve the reliability and efficiency of a communication system, the method comprises the following steps of: constructing a test platform, designing a detection sequence and constructing a statistical model to realize a complete theoretical closed loop from channel feature extraction to modeling. In a data processing and feature extraction stage, a set of efficient signal processing flow is provided, and high-precision time synchronization is realized through cross-correlation calculation of sliding correlation. According to the modeling method, a sine wave superposition algorithm based on LP-Norm is adopted for a Gaussian channel, and fitting of Doppler power spectrum density is achieved by optimizing Doppler coefficients and harmonic parameters. For non-Gaussian characteristics, a sphere invariant process theory is introduced, channel fading is modeled into a product form of a Gaussian process and a heavy-tailed random variable, the combined influence of multipath and shadow effect in an urban environment is captured, and the two fading components are decoupled through Mellin transform. The effectiveness of the method is verified through simulation.

The application relates to the technical field of medical image processing, in particular to a multi-modal lower limb medical image registration method and system based on manifold learning. The method first performs left-right separation on the whole lower limb CT to obtain independent left and right candidate regions; the local MRI is extracted to obtain a limb mask and determine the side. The local image is resampled with the whole resolution as a reference to realize spatial resolution unification. Local block high-dimensional features are extracted, a near neighbor graph is constructed, and a graph Laplace eigenvalue equation is solved to obtain a multi-channel manifold feature map. The representation ambiguity of manifold embedding is eliminated through symbol correction and orthogonal alignment, then Fourier-Mellin transformation is adopted to realize coarse registration, and local refinement is realized in a limited neighborhood. The application completely separates and independently registers the left and right sides, avoids interference of the opposite structure, realizes stable positioning and accurate alignment of the local MRI in the whole lower limb CT.

This invention provides a Fourier-Melin transform image geometric matching method and system with decoupled logarithmic domain, comprising: estimating the rotation angle using Fourier-Melin transform; rotating the image to be matched in the current frame relative to the template image in the previous frame to obtain an axially aligned image search region; transforming the template image and the image to be matched from Cartesian coordinates to logarithmic polar coordinates to obtain the image search region corresponding to the logarithmic polar coordinates; sequentially segmenting the image search regions corresponding to the image to be matched and the template image along the θ-axis according to a set ratio; stitching the horizontally correlated and vertically correlated image regions into two twin image search regions; calculating the cross power spectrum through phase correlation to obtain the scale factors in the horizontal and vertical directions; and aligning the images to be matched according to the scale factors in the two directions. This invention has the ability to estimate scale and rotation proportionally, and is scale adaptive, and is robust to out-of-plane flipping and rotation of the target object.