32results about How to "Restore the truth" patented technology

The invention relates to a method for restoring the three-dimensional structure of a nonwoven material through the central axis of the fiber, extracting the central axis of the fiber through the microscopic image of the multi-layer multi-focal plane nonwoven material in the same field of view, and then restoring its three-dimensional shape and position in the nonwoven material method, multi-layer microscopic image acquisition and fusion, circular segmentation of fibers and selection of center point, calculation of center point depth, extraction of fiber central axis and restoration of the three-dimensional surface of fiber closure; by extracting the source point on the fiber central axis The depth and the cross-sectional radius of the fiber at the source point, and then the three-dimensional coordinates of the fiber axis and the closed surface are restored by spatial interpolation. Compared with other reconstruction methods, the present invention truly restores the longitudinal connection between fibers, and provides high-quality data for subsequent research on key parameters such as pore size and distribution, pore inner surface area, pore volume, air fluid resistance and pressure difference. 3D model.

The invention provides a processing method of a stereo image. The processing method comprises the following steps that: pixel data of all compressed pictures of a stereo image are provided and whether a sum of all pixels of each row of each compressed picture forming the stereo image is equal is determined; when the sum of all pixels of each compressed picture is not equal, a boundary of each picture is determined; received pixel data of all compressed pictures are buffered; one compressed pixel datum that has the minimum number of the column is determined as a pixel datum of column n and onecompressed pixel datum that has the maximum number of the column is determined as a pixel datum of column m; if the number of the column of the pixel data among the compressed pixel data is less thanthe number of the column m, the number of the column of pixel data of the picture is complemented as the number of the column m; and then the pixel data of each picture are decompressed; and last pixel data of the column m-column n of the all decompressed pictures are lost. According to the processing method of a stereo image provided in the invention, the boundary can be determined accurately; the image is restored with reality; and the better user experience can be provided. Besides, the invention also provides a stereoscopic display apparatus with utilization of the processing method of the stereo image.

The invention discloses an image edge classification detection method based on visual path orientation sensitivity. The present invention utilizes the role of neuron synaptic connections in the centripetal distribution of the optimal orientation of the receptive field, constructs a first-level neuron network sensitive to multiple specific directions, uses image pixels as network input, and records neurons in a certain time window The pulse firing sequence within is calculated, and the discharge frequency is calculated as the network output; the network output in multiple directions is fused and mapped to the gray level to form an edge-sensitive image; for the edge-sensitive image, the lateral inhibition range and inhibition amount in the receptive field are determined , form the second-level neuron network, and output the image after lateral suppression; finally, after threshold processing, the edge detection result is obtained. The invention considers important visual mechanisms such as directional receptive fields and lateral inhibition, simulates the hierarchical processing effect of different hierarchical structures on the visual path in contour perception, and can effectively improve the edge detection performance of low-contrast images.

The invention provides a processing method and processing device of remote sensing image data, which are used for solving problems that it is difficult to distinguish ground objects because real geomorphic characteristics in a shadow region are completely or partially shielded during imaging in the prior art. The method comprises the following steps of: for a preset geographic range, obtaining digital elevation model (DEM) data within a geographic range; obtaining a depth image from remote sensing images within the geographic range by using depth image algorithm and mode identification in the digital image processing technology; and fusing the DEM data and the depth image data by using a DEM data fusion processing technology in a geographic information system. By using the technical scheme provided by the invention, the shadow can be eliminated in a comparatively effective way so that contribution is made to really recovering ground object texture so as to distinguish the ground objects.

The invention provides a remote sensing image defogging method based on an edge sharpening cyclic generative adversarial network. According to the method, the foggy remote sensing image is processed by utilizing the deep generative adversarial network, and the ground object information of the foggy remote sensing image can be automatically recovered in a large quantity; secondly, the invention provides a cyclic generative adversarial network model added with an image sharpening mechanism, and the model improves the condition that textures of pictures generated by the generative adversarial network are not clear, and improves the discrimination capability of blurred images; and finally, the VGG16 network pre-training process of calculating the perception consistency loss function by using the model is improved, and the VGG16 network is pre-trained by using the remote sensing image, so that the characteristics of the remote sensing image are better extracted, and the calculation of the perception loss error is more accurate. Compared with an existing remote sensing image defogging method, the remote sensing image defogging method has the advantages of being intelligent, batched and automatic, the quality of the remote sensing image can be remarkably improved, detail information such as remote sensing image textures is protected, and a good recovery effect is achieved.

The invention relates to a method for constructing a road surface depth information model based on a vehicle-mounted mobile laser point cloud, which belongs to the technical field of road surface disease detection, and adopts a section division strategy with overlapping single lanes to control the road surface model. First, the RANSAC algorithm is used to obtain the consistent estimation plane of the single-lane road surface point cloud with a certain length, and the height of the original point cloud is normalized based on this plane; then, the combined filtering method of median filtering and Butterworth low-pass filtering is used to smooth Local high-frequency noise and global vibration noise on the road surface; finally, a quadratic surface model is constructed, and the filtered and smoothed vehicle-mounted mobile laser road surface point cloud is used as the observation value, and the iterative least squares fitting method that suppresses low-frequency features is used to obtain the quadratic surface parameters. Unbiased estimation value, using the continuous quadratic surface model as the standard road surface to calculate the distance from the discrete laser point to the surface to obtain the road surface depth information model. The present invention can restore the road surface structure more realistically, and construct the road surface depth information model.

The invention discloses a method for processing and restoring an audio signal and a system thereof. The method comprises the following steps: using a plurality of audio signal acquisition devices to respectively collect the audio signals from sound sources; determining whether the sound sources exist in the each audio signal acquisition device according to the collected multi-channel audio signals; respectively arranging processing curves to the each channel of the audio signals according to existence of the sound sources in the each audio signal acquisition device; using the arranged processing curves of the each channel of the audio signals to respectively process collected multi-channel audio signals and transmitting the processed multi-channel audio signals; using a plurality of audio signal play apparatuses to respectively receive the corresponding audio signals and playing the received audio signals. Through multi-channel audio acquisition and a processing scheme, restoration of a remote sound field in a video communication system can be realized. Simultaneously, the corresponding audio signal processing curves are used to respectively process the each channel of the audio signals so that the audio signals in a meeting can be accurately and really restored at a far-end.

Embodiments of the present invention provide a stereoscopic image reproduction method, device, device, and storage medium. The method includes: scanning the stereoscopic image to be reproduced based on a preset viewpoint, and obtaining the relative viewpoint of the envelope surface of the sky sphere in the stereoscopic image to be reproduced. The coordinates of the sky envelope surface and the corresponding sky envelope surface texture; obtain the object image coordinates and the corresponding object image texture of the object image in the stereoscopic image to be reproduced relative to the viewpoint; according to the sky envelope surface coordinates and the corresponding sky envelope The surface texture, as well as the object image coordinates and the corresponding object image texture, are restored to generate a stereoscopic image. Through the above technical solution, it is possible to obtain the sky envelope surface coordinates and sky envelope surface texture corresponding to the sky sphere in the stereoscopic image to be reproduced, as well as the object coordinates and object texture corresponding to the object image, so as to restore the stereoscopic image more realistically and accurately . Fixed an issue where recording and restoring stereoscopic images could not be reproduced.