46 results about "Weighted median filtering" patented technology

A method of modeling seismic wave-field data in order to suppress near-surface and sub-surface related multiple reflection signals is provided. The reflection signals include main primary reflection signals, main random noise signals, main multiple reflection signals, residual primary reflection signals, residual random noise signals, and residual multiple reflection signals. Main random noise signals are separated from the reflection signals using a frequency-wavenumber domain method to provide data having suppressed main random noise. Main primary reflection signals are separated from the data having suppressed main random noise using frequency-wavenumber filtering and weighted median filtering to provide data having suppressed main random noise and main primary reflections. Multiple reflection signals are modeled using parabolic path summation on the data having suppressed main random noise and main primary reflections.

The invention discloses a CT image denoising method based on self-adaptive median filtering, belongs to the technical field of medical image processing, and is particularly suitable for CT image denoising of new coronal pneumonia. The method comprises the steps of selecting a square filtering window with the size of n * n, comparing the adaptive maximum value and the adaptive minimum value of the gray value in the window with the gray value f (i, j) of the current pixel point, judging whether the current pixel point is a suspected noise point or not according to a first threshold T0, and if so, further accurately judging whether the current pixel point is a noise point or not according to a second threshold T1, if the current pixel point is not the suspected noise point or the noise point, traversing the next pixel point in the window; processing noise points through a center weighted median filtering method; and finally, outputting the CT image after median filtering and denoising. Image details are better protected while image denoising is kept; the problem that deviation exists in information transmission of a traditional entropy weight method is corrected by improving the entropy weight method, the optimal weight of center weighted filtering is determined through contribution values of all evaluation indexes to the denoising effect, and therefore the optimal denoising effect is achieved.

The invention relates to a stereo matching method based on segmentation cross trees, and discloses a stereo matching method based on segmentation cross trees. The method comprises the following six steps: step one, preprocessing left and right stereo images by use of a Gaussian filtering technology, step two, calculating initial matching cost, step three, constructing a segmentation cross tree for each pixel point to be matched of the left and right stereo images, step four, aggregating the initial matching cost in a segmentation cross tree support area by use of a one-dimensional integration image acceleration technology, step five, calculating parallax errors according to a "winner-take-all" method, and step six, according to the parallax error results of the left and right stereo images, correcting the parallax error results respectively by use of a left-right consistency detection technology and a weight median filtering technology. The method provided by the invention is applied to stereo matching based on the segmentation cross trees.

The invention discloses a wind generating set blade monitoring flaw detection method. Specific to the characteristics of fan blade acquisition images of an unmanned aerial vehicle, an unmanned aerial vehicle camera calibration method, a fast adaptive weighted median filtering algorithm, an image enhancement algorithm, blade surface fault feature extraction and selection, and blade surface fault classification monitoring and identification are used, and embedded into a man-machine interaction platform. Through online and offline tests, the platform can realize automatic identification and monitoring of sand holes, cracks, peeling and other defects, and the accuracy can reach 90% or above; compared with traditional monitoring means and other monitoring algorithms, the platform has higher accuracy and higher algorithm stability; and a new way is provided for nondestructive monitoring of wind driven generator blades.

The invention discloses a mechanical arm intelligent control system based on multi-view stereoscopic vision. The system comprises a mechanical hand and a mechanical hand controller, wherein the mechanical hand controller is in signal connection with the mechanical hand. The periphery of the mechanical hand is fixedly provided with a binocular camera image acquisition unit acting on a target object, and the binocular camera image acquisition unit is connected with an upper computer through a data line; the binocular camera image acquisition unit adopts the improved algorithm combining cross-scale guided filtering with weighted median filtering parallax detailing, three-dimensional reconstruction of the target object is realized, coarse positioning of the target object is completed, and mechanical arm motion trajectory planning is carried out by adopting a 5-3-5 polynomial interpolation trajectory planning method; a monocular camera image acquisition unit is arranged at a clamping jaw ofthe mechanical hand and moves along with a mechanical arm to acquire an image; and the monocular camera image acquisition unit is in communication with the upper computer through a wireless transmission module, and the monocular camera image acquisition unit adopts a template matching method based on SURF for accurately positioning the target object.

The present disclosure relates to image filtering techniques for enhancing image quality. In one embodiment, two filtering techniques are applied on an image. Firstly, an adaptive weighted median filtering operation is performed on an acquired low contrast image corrupted by impulsive noise. Subsequently, a guided image filtering on the image obtained from adaptive weighted median filtering operation to de-blur and enhance the contrast that ultimately assures to preserve the edges of the images. In addition, the image filtering for enhancing image quality is enhanced by several variations of data adaptive guided image filtering and adaptive window sizes for guided image filtering techniques.

The invention relates to an infrared image noise removal method based on adaptive weighted median filtering. The method comprises the following steps: 1, establishing an infrared image self-adaptive median filtering noise removal method; and 2, distinguishing whether a processing object is noise or image details by utilizing an image gray variance, and finally realizing adaptive median filtering denoising of the infrared image through a center weighting mode, so that the method greatly ensures edge detail information of the image under the condition of removing background noise of the infraredimage, and has a relatively high application value.

The invention discloses an iterative depth map structure restoration method based on RGB-D SSIM structure similarity. First, the edge of the input depth map is detected, and the edge is expanded, and the expanded area is marked as a potential structural distortion area, and then the Each pixel in the potential structural distortion area judges whether it is distorted, and generates a structural distortion metric index. The distorted pixel uses the product of the Gaussian weight of the color image and the structural distortion metric index to construct a restoration weight, and performs guided restoration through a weighted median filter, and then The distorted area is guided and filtered, and the completed result map continues to iterate according to the above steps until the set termination iteration condition is met, and the depth map is output to end the calculation. The present invention obtains more accurate structural information by iteratively detecting and recovering the structurally distorted area of ​​the depth map, and at the same time denoises and preserves the edges of the structurally undistorted area, finally obtaining a depth map with a clear structure and smooth depth values .

The invention discloses a CT image denoising method based on adaptive median filtering, belongs to the technical field of medical image processing, and is particularly suitable for CT image denoising of new coronary pneumonia. Select a square filter window with a size of n×n, compare the adaptive maximum and adaptive minimum of the gray value in the window with the current pixel gray value f(i,j), according to the first threshold T 0 Judging whether the current pixel point is a suspected noise point, if so, according to the second threshold T 1 Further accurately judge whether it is a noise point; if the current pixel point is not a suspected noise point or a noise point, traverse the next pixel point in the window; process the noise point through the center weighted median filter method; finally output the median filter to denoise After CT image. While maintaining image denoising, the image details are better protected; the problem of information deviation in the traditional entropy weight method is corrected by improving the entropy weight method, and the optimal value of the center weighted filter is determined by the contribution value of each evaluation index to the denoising effect. optimal weight to achieve the best denoising effect.

The invention provides a real-time weighted median filtering method based on a bilateral grid. The method mainly comprises five steps that an input image and a boundary image are given by a user; a four-dimensional bilateral grid having x, y, z and a four coordinate axes are constructed according to the input image and the boundary image; according to the constructed four-dimensional bilateral grid, Gauss filtering operation is carried out respectively along the x, y and z coordinate axes to acquire a bilateral grid after smoothing weighting; according to the bilateral grid after smoothing weighting, accumulation operation long the a coordinate axis is carried out to acquire a three-dimensional histogram after accumulation; according to the three-dimensional histogram after accumulation, the final weighted median filtering output image is acquired on the basis of a linear interpolation method. On the basis of advantages of the bilateral grid, not only can image smoothing filtering be realized, but also the relatively good edge information is further kept. According to the method, each step can be parallelly processed in the graphic card hardware, and the operation speed is effectively improved.

The invention discloses an SAR image edge detection method based on the anisotropic morphology direction ratio, and mainly solves a problem that the edge detection is poor in robustness of discrete strong-scattering points in the prior art. carrying out the anticlockwise rotation of Gaussian gamma-shaped double windows, and carrying out the weighted median filtering of the Gaussian gamma-shaped double windows; calculating the multi-direction edge response through the median filtering, and carrying out the multi-direction edge response; calculating the edge intensity mapping according to the edge response; extracting a maximum value point from the edge intensity mapping as a candidate edge point; carrying out the double-threshold decision making of the candidate edge point, and obtaining an edge detection result of a final image. According to the invention, the method achieves the improvement of the robustness of the SAR image edge detection for discrete strong-scattering points, meets the real-time requirements of the SAR image edge detection in a large scene, and can be used for the extraction of the SAR image edge in the big scene comprising the discrete strong-scattering points.