11results about How to "Remove blur" patented technology

The invention relates to a high squint SAR imaging processing method under Doppler frequency distance time varying. The method comprises the following steps: firstly, carrying out linear walking correction and distance compression according to a squint angle; then distance partitioning and azimuth upsampling are carried out according to the pulse repetition frequency, the instantaneous Doppler bandwidth and the Doppler frequency time-varying quantity along with the distance, azimuth spectrum ambiguity caused by the change of the Doppler center frequency along with the slope distance is eliminated through azimuth spectrum extension, and sub-block splicing is carried out after upsampling of all sub-blocks is completed; carrying out azimuth space-variant resampling in a two-dimensional frequency domain, and eliminating azimuth space-variant in a range gate; then consistent compression and stot interpolation are carried out, and two-dimensional accurate focusing is completed; and finally, correcting image distance position time shift caused by linear walking correction, and intercepting an effective imaging area to obtain a focused SAR image. According to the method, the Doppler spectrum fuzzy problem caused by Doppler frequency distance time variation can be effectively eliminated, so that effective application of a traditional large squint algorithm is ensured, and a correctly focused SAR image is obtained.

The invention discloses an earth surface exposed geologic body reality sense three-dimensional reconstruction method based on a neural radiation field. The method comprises the steps that an earth surface geologic body image data set is acquired; performing feature matching on the image data set by using a feature matching strategy based on a nearest neighbor algorithm and a LightGlue neural network to generate feature point matching information and a feature description file; sparse three-dimensional point cloud data and camera pose information are obtained based on incremental SfM; and obtaining depth information of an image data set based on sparse three-dimensional point cloud data and camera pose information, and establishing a geologic body realistic three-dimensional reconstruction model by using a neural radiation field optimization method fusing the depth information and Gaussian position coding. According to the method, the feature matching precision and the camera pose calculation accuracy are improved, the texture detail expression ability of a geological structure can be improved, the reconstruction quality of a surface geologic body model is enhanced, and geological information support can be provided for the fields of geological research and engineering application.

The invention provides a deep learning-based turbid underwater image restoration method, which comprises the following steps: establishing a CycleGAN cyclic consistency network model, respectively adding attention modules in an encoder and a decoder to optimize the model so as to enhance the detail extraction ability of the model, the attention modules comprising simAM and MLCA, and training the CycleGAN cyclic consistency network model by using the data set, adjusting the model configuration, adding a loss function and an optimizer, and performing image quality and visual effect evaluation on the processed image of the CycleGAN cyclic consistency network model. By means of the mode, the problems of blurring, distortion and noise in the underwater image can be better solved, the restored image is clearer and more accurate, the underwater image processing efficiency and quality can be improved, and development of the fields of underwater exploration, underwater archaeology, underwater robots and the like can be promoted.

The invention relates to the technical field of television image communication, in particular to an anti-explosion conference television system and a conference television implementation method. The method comprises the following steps: acquiring an original conference image stream through multi-source image acquisition, performing displacement compensation and multi-resolution fusion, generating a standardized image stream, simulating conference communication transmission, checking image feature quality, deducing equipment load, analyzing the bearing capacity of the explosion-proof conference television, and obtaining a bearing capacity change curve; and according to the curve, screening out a limit load point, carrying out load reduction segmentation, generating a low-load image stream, carrying out path redistribution on the low-load image stream, forming a path distribution matrix, and realizing real-time transmission so as to ensure effective operation of the explosion-proof conference television. According to the invention, a safer and more efficient explosion-proof conference television realization method is realized.

This invention discloses a method and system for designing a spatiotemporal database of land value, applied in the fields of spatial geographic information data processing and image correction technology. The method involves acquiring spectral remote sensing image data; performing geographic coordinate matching on the spectral remote sensing image data to generate coordinate spectral remote sensing image data; digitally rasterizing the spectral remote sensing image data using a digital elevation model to generate point cloud data; performing 3D reconstruction based on the point cloud data to obtain a 3D terrain model; performing boundary region reconstruction processing on the 3D terrain model to obtain a reconstructed model; extracting ground features from the reconstructed model to obtain ground feature data; and constructing a spatiotemporal database by spatiotemporally indexing the ground feature data. This method can correct the brightness of edge defects of interval-type and linear ground features based on predicted brightness changes, significantly reducing grayscale distortion in 3D images and eliminating blurring caused by interference.

The present application is applicable to the field of temperature detection of microelectronic devices based on optical principles, and provides a method and device for automatic refocusing of thermal reflection thermal imaging based on dual-area detection, the method comprising: based on the reference image and the temperature change of the measured object, obtaining the first area and the second area of ​​the reference image, calculating the clarity of the two areas, and adjusting the three-axis nano-displacement stage; after each adjustment of the three-axis nano-displacement stage, obtaining the current measurement image, calculating the clarity of the two areas; the current measurement image still contains the above two areas; if the temperature of the measured object, the displacement of the three-axis nano-displacement stage, and the clarity of the second area meet the preset temperature threshold condition, the second preset displacement threshold condition, and the second preset clarity condition, and meet the first preset displacement threshold condition and the first preset clarity condition, determine the measurement result. The present application can improve the accuracy of the temperature measurement results and lay the foundation for realizing photothermal reflection imaging temperature measurement at high spatial resolution.

The invention discloses an underwater target detection and positioning method and system based on a passive sonar array, and relates to the technical field of underwater acoustic signal processing. Acoustic signals radiated by an underwater target are received and divided into dense subarray data and sparse subarray data; performing a sparse Bayesian learning algorithm on the sparse subarray data, and outputting a high-precision fuzzy value; carrying out azimuth estimation on the dense subarray data in a full-angle range through a dense part to obtain a low-precision unambiguous value; and fusing the high-precision fuzzy value and the low-precision non-fuzzy value through an estimation matching model to obtain an orientation estimation result of the underwater target. According to the method, high-precision azimuth estimation is carried out based on the combination of the ternary co-prime array and the compressed grid sparse Bayesian learning, high-precision (but fuzzy) estimation is carried out by utilizing the sparse part of the TCA array, low-precision (but non-fuzzy) estimation is carried out by utilizing the dense part, and high-precision target azimuth estimation under low operand is realized.

The application provides an underwater fixed-distance luring camera device for shrimp culture, and relates to the technical field of aquaculture monitoring equipment. The underwater fixed-distance luring camera device comprises a water control terminal and an underwater collecting unit. The underwater collecting unit comprises a support connecting arm, and the support connecting arm is provided with an underwater camera module, a light supplementing assembly and a luring module. An observation cover plate is arranged on the shooting direction of the underwater camera module. A feeding outlet of the luring module is arranged towards the disc surface of the observation cover plate, and is used for feeding bait on the observation disc. The water control terminal comprises an intelligent main control terminal and an antenna. The application physically locks the shooting area in the best focal length range of the camera by using the observation cover plate, and enhances the picture by combining with an algorithm, so that the technical problem that ordinary cameras are difficult to capture clear images under water due to the fast swimming speed and uncertain position of shrimps is effectively solved.

The invention discloses a method for estimating a wave direction and a wave period from an X-band radar image, and the method comprises the steps: dividing each X-band radar image into a plurality of sub-images, extracting the texture features of the sub-images through two-dimensional empirical curve transformation (2D-ECT), and decomposing the sub-images into a plurality of two-dimensional curve components; selecting a curvelet component with the highest relevancy with the sub-image, and estimating a wave direction by using empirical ridge transform (ERT); meanwhile, 180-degree ambiguity of the wave direction is eliminated by using a cross correlation coefficient; in order to estimate a wave period, calculating a periodogram power spectrum by the sub-images after the texture features are extracted; then, obtaining the frequency corresponding to the maximum power spectral density in the azimuth angle pixels of the sub-images, and estimating the wave period through the reciprocal of the frequency; according to the estimation method, the sea wave texture features can be effectively obtained, and an effective means and method are provided for obtaining high-precision sea wave directions and wave periods.

The present application belongs to the electronic information, signal processing, communication and radar positioning cross technical field, and relates to a signal delay measurement method, system and terminal. The present application collects the transmitting signal and the receiving signal through the delay system, respectively makes the fast Fourier transform on the two signals and selects the frequency interval according to the spectrum, and then calculates the phase difference change; at the same time, a new phase unwrapping method is proposed to solve the 2pi phase ambiguity problem caused by the calculation of the phase difference, and the phase difference is shifted and corrected to restore it to the phase difference corresponding to the high frequency; finally, the delay in the time domain of the two signals is used, which is priori information that the phase difference is proportional to the frequency in the frequency domain, and the phase difference points of the selected frequency interval are forced to pass through the origin linear fitting, and the delay is calculated through the slope of the straight line. The present application avoids the error accumulation caused by noise or phase mutation, and significantly improves the delay estimation robustness under the condition of low signal-to-noise ratio or frequent phase jump.

The present invention discloses a method and a detection system for accurately depicting groundwater pollution, and relates to the field of groundwater detection technology. The method comprises the following steps: S1, by opening an observation well in the area to be detected, the detection equipment is submerged into the target water area; S2, the water body information, survey video and location information of the target water area are collected in real time by the detection equipment; S3, based on the water body information and location information, the regional pollution index at different locations in the target water area is analyzed; S4, based on the survey video and location information, the water quality status at different locations in the target water area is identified; S5, the pollution distribution of the target water area is depicted by combining the geographic information system and the pollution distribution model. The present invention provides reliable technical support for the monitoring and control of groundwater pollution, so as to accurately evaluate the pollution degree of the groundwater detection point, especially for non-aqueous phase liquid pollutants, so as to carry out targeted extraction and treatment.