13 results about "Curvelet transform" patented technology

Curvelet-based low level fusion of camera and RADAR sensor information is disclosed and includes processing RADAR data corresponding to a scene to generate a RADAR point cloud and processing camera image data corresponding to the scene using a curvelet transform to identify a target of interest in the scene and generate for the target of interest a target type, (x,y) coordinate values, and a curvelet magnitude per decomposition level. If discrepancies exist between (x,y) coordinate values of the RADAR point cloud and the target type, (x,y) coordinate values, and curvelet magnitude per composition level of the target of interest, a portion of the RADAR data processing is repeated to regenerate the RADAR point cloud; otherwise, the RADAR point cloud to a perception stack of a vehicle.

The application relates to the technical field of petroleum geophysical exploration processing, and provides a method, device, equipment, medium and product for improving the signal-to-noise ratio of reconstructed data, which is characterized in that the signal-to-noise ratio of each trace of a target layer in an irregular observation system is calculated as the signal-to-noise ratio of the target layer, a three-dimensional array is constructed for data of a regular observation system designed based on the irregular observation system, the three-dimensional array is valued based on the irregular observation system, the three-dimensional array after the valuation is calculated based on three-dimensional curvelet transformation, and re-valuation is performed according to the signal-to-noise ratio of the data of the target layer of adjacent traces; the use proportion of high signal-to-noise ratio data in the reconstruction process is improved; after iterative calculation, the reconstructed data is output; the continuity constraint in each direction and the signal-to-noise ratio information of the target layer in the three-dimensional data can be fully utilized; the use proportion of high signal-to-noise ratio data in the reconstruction process is improved; and the signal-to-noise ratio of the reconstructed data is improved, thereby meeting the demand of exploration production.

The invention provides a noise channel identification and reconstruction method and device based on multi-attribute fusion. The method comprises the following steps: configuring a seed gun according to a geological task, dividing a plurality of region sets by taking an excitation point as a center, determining a time window range of a seismic channel in a region through spatial interpolation of a seed gun first arrival wave time window, and generating seismic channel data. And analyzing the signal energy of the first arrival wave time window and the noise time window, carrying out anomaly identification in combination with statistical characteristics, and if abnormal, dividing the abnormal channels into abnormal channels and carrying out zero filling processing. Constructing a three-dimensional data volume, and performing multi-scale curvelet transformation on the three-dimensional data volume to obtain a curvelet coefficient; and carrying out iteration on the curvelet coefficient to realize reconstruction of the seismic channel, and correcting the amplitude of the reconstructed seismic channel through spatial interpolation to obtain reconstructed shot domain data so as to complete identification and reconstruction of the noise channel. According to the method, the abnormal channels are effectively eliminated, the quality of the seismic data with the low signal-to-noise ratio is improved, and a reliable data basis is provided for high-precision imaging under complex geological conditions.

This invention pertains to data processing technology for seismic exploration of sandstone-type uranium deposits, specifically an adaptive denoising method for sandstone-type uranium deposit seismic data based on sparse transform. The method includes: inputting noisy raw two-dimensional seismic data y; initializing the maximum number of iterations I, setting the outer iterative accumulator i=1, and designing a search range J for the denoising coefficient truncation percentage; for each i, calculating the curvelet transform coefficients s of y; for each j within the search range, applying hard thresholding for denoising, and performing an inverse curvelet transform on the denoised coefficients to obtain the denoised seismic data y. j ; Calculate the noise removal ε corresponding to each j j The entropy; compare the calculated noise ε removed for each j. j The entropy is calculated, and the percentage corresponding to the maximum entropy within the search range is taken as the optimal denoising effect, and the corresponding seismic data is output. If i reaches the maximum number of iterations, the loop is exited, and the denoised seismic data corresponding to the current maximum entropy value is used as the output result. This invention can protect the effective signal while suppressing random noise.

The invention provides a multiple suppression method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring seismic data; curvelet transformation parameters are obtained; transforming the seismic data into a curvelet domain by using a curvelet transformation technology based on the curvelet transformation parameters; according to the distribution positions of the multiples in the curvelet domain, curvelet plates of the multiples distributed in the curvelet domain are removed, and primary curvelet plates are obtained; and performing anti-curvelet transformation on the primary curvelet plate to obtain seismic data after multiple suppression. The method comprises the following steps: transforming seismic data into a curvelet domain by utilizing a curvelet transformation technology, and separating and suppressing multiples in the curvelet domain by utilizing curvelet transformation parameters according to the principle that the characteristics of the multiples are different from the characteristics of primary waves. Compared with other multiple suppression methods, the method has the advantages of being high in operation efficiency, good in suppression effect, accurate in multiple recognition and high in denoising fidelity.

The embodiment of the invention relates to the technical field of data processing, and discloses a data denoising method and device, electronic equipment, a storage medium and a program product, and the method comprises the steps: obtaining to-be-processed DAS data in a mining area environment; curvelet transformation is carried out on the to-be-processed DAS data to obtain a curvelet coefficient set, the curvelet coefficient set corresponds to multiple scales, the multiple scales comprise at least one key scale, and the at least one key scale is determined based on a frequency band to which an effective signal in the mining area environment belongs; the density of multiple directions corresponding to each key scale in a key direction range is higher than the density in a non-key direction range, and the key directions are determined based on geological features of a mining area environment; performing denoising processing on the curvelet coefficient set to obtain a denoised curvelet coefficient set; and generating first DAS data based on the de-noised curvelet coefficient set. In this way, the quality of the DAS data is improved.

The invention provides an infrared image enhancement method and device based on histogram matching and curvelet transformation. The method comprises the following steps: acquiring a to-be-enhanced infrared image and a reference image; respectively calculating a gray average value and a gray standard deviation of the infrared image and the reference image; calculating a correction coefficient and an average correction value based on the gray average value and the gray standard deviation; generating a histogram matching enhanced image of the infrared image based on the correction coefficient and the average correction value; curvelet transform decomposition is carried out on the histogram matching enhanced image and the infrared image to obtain corresponding multi-scale and multi-direction sub-band coefficients, and fusion is carried out on the corresponding sub-band coefficients under the same scale and the same direction to obtain a fusion sub-band coefficient; and performing curvelet inverse transformation on the fusion sub-band coefficient to obtain a fusion enhanced image. According to the invention, through the cooperation of the global gray correction of histogram matching and the local detail fusion of curvelet transformation, the contrast, definition and detail information of the infrared image are synchronously improved.

The invention discloses a data processing method, electronic equipment, a storage medium and a computer program product, and the method comprises the steps: converting first seismic data into corresponding first wave field data; curvelet transformation is carried out on the first wave field data to obtain a first curvelet coefficient set; extracting one or more first curvelet coefficients corresponding to a first diffracted wave from the first curvelet coefficient set through a first model; and processing the one or more first curvelet coefficients to obtain an image of the first diffracted wave. Through the method and the device, the diffracted waves in the seismic data can be separated more accurately, so that the imaging precision of the diffracted waves is improved.

This disclosure relates to the field of computer technology, and particularly to a gather repair method, apparatus, device, storage medium, and computer program. The gather repair method includes: acquiring seismic data, the seismic data including multiple seismic coordinate points, the seismic coordinate points being the coordinate points where earthquakes occur, and the seismic coordinate points being located in a Cartesian coordinate system; extracting curvelet coefficients corresponding to at least one spatial parameter of the seismic data based on a curvelet transform algorithm to obtain at least one curvelet coefficient; acquiring source-receiver offset vector surface element (OVT) gathers corresponding to the at least one curvelet coefficient, the OVT gathers being seismic data with the same spatial information; extracting anisotropy parameters of each curvelet coefficient, and using the anisotropy parameters of each curvelet coefficient to repair the corresponding OVT gathers, obtaining target OVT gathers corresponding to each OVT gather. The embodiments of this disclosure improve the accuracy of gather repair.

The invention discloses a first arrival refraction area linear interference suppression method, a product, a medium and equipment, and belongs to the technical field of seismic data processing. The method comprises the following steps: designing different parameters aiming at inconsistent linear characteristics of different frequency band ranges; the multi-scale and multi-directional representation capability of curvelet transform is utilized to decompose seismic data into subsets with different scales and directions, and then accurate wave field separation is realized through Radon transform in each curvelet domain, so that refraction interference with relatively strong energy in a first arrival refraction region is eliminated, and effective reflection signals in a large offset range are recovered. The method can accurately suppress first-arrival refraction interference, recover effective signals, and improve seismic imaging quality.

The application discloses a kind of multi-sampling rate seismic data volume reconstruction method and device.The method includes, according to multi-sampling rate seismic data volume, establish observation system regular empty data volume, assign the data of matching way in seismic data volume or set initial value for the way therein, constitute initial data volume;Initial data volume is divided into multiple small data volumes, one-dimensional Fourier transform of time variable is carried out to each small data volume, and the data volume of f-x-y domain is obtained;For each f-x-y domain data volume, the transformed data volume is obtained by three-dimensional curve wave iterative transformation;The initial reconstruction data volume is obtained by combining the transformed data volume;According to seismic data volume, the initial reconstruction data volume is corrected, and the reconstruction data volume is obtained.The curve wave transformation of three-dimensional seismic data volume is carried out in f-x-y domain using split beam, the problem of large memory occupation in large data volume three-dimensional curve wave transformation is solved, and the reconstruction of multi-sampling rate seismic data can be completed with high fidelity and high efficiency.

The present disclosure relates to the technical field of image analysis, and provides an image analysis method and device. The method comprises: acquiring an original image containing a target to be recognized; introducing the original image into a preset recognition model to recognize a target rectangular region; cutting a target sub-image from the original image based on the target rectangular region; performing multi-resolution curvelet transform on the target sub-image to generate a target feature vector; and comparing the target feature vector with a preset template feature vector to determine whether the target to be recognized in the original image is abnormal. The embodiments of the present disclosure can determine the state of the insulator in the whole and in the details synchronously, thereby greatly improving the accuracy and effectiveness of the analysis result.

The application provides an infrared image enhancement method and device based on histogram matching and curvelet transform. The method comprises: acquiring an infrared image to be enhanced and a reference image; calculating the gray mean value and the gray standard deviation of the infrared image and the reference image respectively; calculating a correction coefficient and an average correction amount based on the gray mean value and the gray standard deviation; generating a histogram matching enhanced image of the infrared image based on the correction coefficient and the average correction amount; respectively performing curvelet transform decomposition on the histogram matching enhanced image and the infrared image to obtain corresponding multi-scale and multi-direction sub-band coefficients, and fusing corresponding sub-band coefficients at the same scale and the same direction to obtain fused sub-band coefficients; and performing curvelet inverse transform on the fused sub-band coefficients to obtain a fused enhanced image. Through the cooperation of the global gray correction of histogram matching and the local detail fusion of curvelet transform, the application realizes the synchronous improvement of the contrast, the definition and the detail information of the infrared image.