32results about How to "Avoid estimated impact" patented technology

The invention provides a magnetic resonance diffusion tensor de-noising method and a magnetic resonance diffusion tensor de-noising system. The method comprises the following step: based on a magnetic resonance diffusion-weighted imaging model and Gaussian distribution properties of sampling noises, obtaining a de-noised diffusion tensor matrix corresponding to each spatial position from K spatial data through a maximum posterior probability estimation method by utilizing sparsity of a dispersion tensor characteristic value. According to the magnetic resonance diffusion tensor de-noising method disclosed by the invention, influence of image de-noising errors to diffusion tensor estimation can be avoided, noises in diffusion tensor can be effectively restrained, and estimation precision of the diffusion tensor can be improved.

The invention provides electronic image stabilization method and device of the vehicle-mounted camera and readable storage medium. The method comprises determining a moving object recognition area ofa first reference image collected at the last moment and a plurality of feature points in an area outside the moving object recognition area of the first reference image; obtaining reference points corresponding to the feature points from a second reference image collected at the current moment; determining a first affine transformation matrix according to each feature point and each correspondingreference point; determining a compensation parameter according to a difference value between an observed quantity and a state quantity in the first affine transformation matrix; determining a secondaffine transformation matrix according to the compensation parameter, transforming the second reference image through the second affine transformation matrix to obtain the stable image at the current moment, and therefore the feature points in the moving object recognition area where the moving object in the image is located are removed, the influence of the moving object on moving parameter estimation is avoided, and the image stabilization accuracy is improved.

The present invention provides a magnetic resonance diffusion tensor denoising method and system. The method is based on the magnetic resonance diffusion weighted imaging model and the Gaussian distribution property of the sampling noise, utilizes the sparseness of the relative anisotropy of the diffusion, and adopts the maximum a posteriori probability estimation The method of K-space directly obtains the denoised diffusion tensor matrix corresponding to each spatial position. The invention can avoid the influence of the image denoising error on the estimation of the diffusion tensor, suppress the noise in the diffusion tensor more effectively, and improve the estimation precision of the diffusion tensor.

The invention relates to a cyclic correlation channel estimation method and device. The method comprises the following steps: S110, providing a cyclic sequence set [CH1 CH2], wherein the content of the sequence CH1 is the same as the content of the sequence CH2; S120, performing channel estimation for the cyclic sequence set [CH1 CH2] through cyclic shift to obtain a time-domain channel h; S130, performing FFT for the time-domain channel to obtain a frequency-domain channel H; S140, adjusting the amplitude of the frequency-domain channel to ensure that the signal effective value RMS(h) of the frequency-domain channel is equal to RMS(H); and S150, performing interpolation calculation for the adjusted frequency-domain channel, and filtering to obtain a channel estimation value. According to the cyclic correlation channel estimation method and device disclosed by the invention, the problem that a single carrier communication system is difficult to quickly estimate the amplitude and phase information of each path in multi-path channels can be solved.

The invention discloses a rigid target three-dimensional motion estimation method in a multi-view environment, and is specifically implemented according to the steps of: 1. building a multi-view target image acquisition environment, and obtaining a plurality of target images; 2. rebuilding a target three-dimensional shape S(t) according to the plurality of target images that are obtained in the Step 1, and initializing motion parameters of the target three-dimensional shape S(t); 3. building an energy function E which reflects distance between a multi-view two-dimensional projection of the target three-dimensional shape and the target images, judging whether the energy function E converges, if not, turning to Step 4, and if yes, outputting the motion parameters of the target three-dimensional shape S(t), i.e., the motion parameters of a rigid target three-dimensional shape S(t); and 4. updating the motion parameters of the target three-dimensional shape S(t), and turning to the Step 3. Estimation of target three-dimensional motion by the method is not influenced by illumination variation and chromatic aberration of a camera.

The invention provides a denoising method and a denoising system for magnetic resonance diffusion tensor imaging. The method is based on a magnetic resonance diffusion-weighted imaging model and the Gaussian distribution properties of sampled noise, and comprises obtaining a denoised diffusion tensor matrix corresponding to each spatial position from K spatial data directly by virtue of the sparsity of the mean diffusivity and by use of a maximum posterior probability estimation method. The denoising method is capable of avoiding the influence of the image denoising errors on diffusion tensor estimation, and further capable of more effectively inhibiting the noise in the diffusion tensor and improving the estimation accuracy of the diffusion tensor.

The invention discloses a channel estimation method and a channel estimation device. The channel estimation method includes the following steps: a pilot frequency sub-carrier distance and an insert position deviation value of pilot frequency symbols in adjacent frequency domains are determined; according to the pilot frequency sub-carrier distance and the insert position deviation value of the pilot frequency symbols in adjacent frequency domains, the pilot frequency symbols in the frequency domains are inserted in effective sub-carriers corresponding to the frequency domain pilot frequency symbols; according to a frequency domain symbol sequence obtained after inserting processing, time domain pilot frequency symbols are determined; and the time domain pilot frequency symbols are transmitted, so that an opposite end carries out channel estimation according to the time domain pilot frequency symbols after receiving the time domain pilot frequency symbols. By means of the channel estimation method and the channel estimation device, influences on transmission from frequency deviation and channel time-varying characteristics can be avoided, and the accuracy of the channel estimation is improved.