8 results about "Gaussian image" patented technology

The embodiment of the invention discloses an automatic image registration method and device for tissue slices and electronic equipment. The method comprises the following steps: acquiring a target dyed image obtained by preprocessing a tissue slice, and generating a honeycomb image corresponding to the tissue slice; constructing a multi-layer Gaussian image pyramid for the target dyed image and the cellular image; and carrying out angle and position search layer by layer from a low-resolution layer to a high-resolution layer in the multi-layer Gaussian image pyramid, determining a target registration parameter corresponding to the highest-resolution layer, and carrying out registration on the target dyed image and the honeycomb image according to the target registration parameter. In the embodiment of the invention, the optimal registration parameter can be comprehensively evaluated layer by layer through a multi-dimensional scoring mode, the limitation of a traditional correlation method is overcome, the algorithm adaptability is better, and the precision of automatic registration is higher.

The application discloses a dense optical flow-based optical remote sensing image uniform dense matching method and system, equipment and a storage medium, and belongs to the technical field of satellite remote sensing image processing. The application solves the technical problem that the prior art lacks a dense optical flow-based optical remote sensing image uniform dense matching method which can recognize sufficient and uniformly distributed matching points in various complex scenes and has high positioning accuracy. The application confirms a remote sensing image overlap area, divides the remote sensing image overlap area into a plurality of remote sensing image blocks, constructs a displacement field solving model and a Gaussian image pyramid, obtains a displacement field of the remote sensing image overlap area, acquires a pre-matching matching point pair set, distributes the pre-matching matching point pair set into corresponding remote sensing image overlap area image blocks, and screens a final matching point set. The application is used for realizing a dense optical flow-based optical remote sensing image uniform dense matching method which can recognize sufficient and uniformly distributed matching points in various complex scenes and has high positioning accuracy.

The application discloses an image edge detection method and device, equipment and a storage medium, and relates to the technical field of computer vision. The method comprises the following steps: if an initial image input by a user is received, performing Gaussian filtering on the initial image to obtain a Gaussian image; gradient information of each pixel point in the Gaussian image is acquired; a target edge threshold corresponding to the Gaussian image is determined according to the gradient information; each edge point is screened out from the pixel points according to the target edge threshold; and the edge image of the initial image is obtained by connecting the edge points. The application solves the technical problem of low image edge detection efficiency.

The invention discloses a three-dimensional scene reconstruction method, electronic equipment and a vehicle, and the method comprises the steps: obtaining an initial four-dimensional Gaussian according to an initial all-around image collected by a camera of a vehicle, a camera pose corresponding to the initial all-around image, and a camera internal reference; according to the position information of the vehicle, the camera pose, the camera internal reference and the acquisition time of the initial look-around image, obtaining an initial motion field; according to the initial four-dimensional Gaussian and the initial motion field, obtaining a rendering result corresponding to the collection moment; adjusting parameters in the initial four-dimensional Gaussian and the initial motion field according to the rendering result and the initial look-around image to obtain a target four-dimensional Gaussian and a target motion field; and the target three-dimensional scene is constructed according to the target four-dimensional Gaussian and the target motion field, so that the three-dimensional reconstruction of the dynamic scene is carried out only through the image acquired by the camera of the vehicle and the calibration parameter of the camera without a point cloud and a three-dimensional marking frame, and the three-dimensional scene reconstruction efficiency is improved.

This invention relates to the field of image data processing technology and discloses an image data processing method based on AOI defect feature extraction, comprising: constructing a Gaussian image sequence of the image to be detected using a preset step size; calculating the Hessian matrix of the pixel position for each scale image and extracting the principal feature vector, and determining the inter-scale directional coherence coefficient characterizing the geometric orientation stability; sampling along the normal space of the principal feature vector, calculating the discrete measure characterizing the isolation degree of feature distribution, and suppressing periodic background texture; and modulating the response intensity using the directional coherence coefficient. This invention utilizes the geometric stability and spatial distribution density differences during the scale evolution process to achieve the essential separation of industrial background texture from weak structural defects, effectively suppressing background random noise interference, and improving the linear separability and detection stability of defect features in the feature space.

A telecentric interferometer, a method for determining characteristics of an incident light field, and an interferometer assembly are disclosed. The telecentric interferometer includes a front optical element having an exit pupil, a first optical system having a first interferometer arm, a second optical system having a second interferometer arm, a detector, and a shift unit positioned between the front optical element and the detector. The first optical system and the second optical system have identically positioned object-side principal planes with the same object-side focal length, the same Gaussian image distance, and the same object-side optical axis. The exit pupil of the front optical element is separated from the object-side principal plane by the object-side focal length. The shift unit shifts the image-side principal plane of the first optical system and / or the image-side principal plane of the second optical system so that the image-side principal plane of the first optical system is different from the image-side principal plane of the second optical system and the optical path length of the first interferometer arm is equal to the optical path length of the second interferometer arm.

The invention discloses a bridge vibration detection method and system based on a visual technology, and belongs to the technical field of bridge vibration detection, and the method comprises the following steps: S1, obtaining vibration displacement data of a target bridge; s2, analyzing vibration displacement data; and S3, evaluating the structural performance and the safety state of the bridge. The speed of the NCC algorithm is increased by using the Gaussian image pyramid method, the accuracy of the NCC algorithm is improved by using the template matching algorithm improved by the quadric surface fitting algorithm, and the vibration of the bridge can be monitored, analyzed and identified in real time, so that the evaluation of the structural performance and the safety state of the detected bridge is realized.

The invention provides a method and a device for detecting a pipeline welding seam image, relates to the technical field of image processing, and can improve the accuracy of pipeline welding seam detection. The method comprises the following steps: acquiring an initial pipeline welding seam image; gaussian blur processing is carried out on the basis of the initial pipeline welding seam image, a first Gaussian image is obtained, the first Gaussian image comprises low-frequency region information, and the low-frequency region information is information with the change amplitude, changed along with the spatial position, in the initial pipeline welding seam image smaller than a preset amplitude threshold value. And performing logarithmic transformation based on the first Gaussian image to obtain a first logarithmic image, and performing logarithmic transformation on the initial pipeline welding seam image to obtain a second logarithmic image. Signal separation is conducted on the basis of the first logarithmic image and the second logarithmic image, a target image is obtained, the pipeline welding seam is detected on the basis of the target image, the target image comprises high-frequency area information, and the high-frequency area information is image information of the pipeline welding seam in the initial pipeline welding seam image.