13 results about "Image geometry correction" patented technology

The invention discloses a farmland furrow three-dimensional point cloud data correction method and system based on a laser radar, and relates to the technical field of three-dimensional image processing based on the laser radar, in particular to a three-dimensional image geometric correction technology. The problems that original point cloud data directly obtained under the dynamic operation condition of an existing agricultural machine has geometric distortion, and the shape of a furrow cannot be truly reflected are solved; meanwhile, the problems that furrow quality evaluation seriously depends on low-efficiency manual means, the adaptability of an existing automatic technical scheme to an unstructured field environment is insufficient, and robust, real-time and high-precision perception of a real three-dimensional shape of a furrow cannot be achieved are solved. According to the method, dynamic tilt correction is carried out through real-time acquisition of point cloud and agricultural machine attitude information, boundary feature points are extracted, boundary lines are fitted, and a three-dimensional point cloud set of a single furrow is reconstructed by fusing a self-adaptive clustering algorithm of spatial prior. The method is suitable for the fields of farmland tillage and soil preparation quality detection, precision agricultural management, agricultural machinery intelligent operation and the like under the dynamic operation condition of agricultural machinery.

The invention provides a three-dimensional image modeling method and device based on plane data, and the method comprises the steps: carrying out the full-color / multispectral band fusion, bit depth adjustment, thin cloud removal, image enhancement, stripe removal and light and color uniformity of a satellite surveying and mapping image, and achieving the real color recovery of the image; performing splicing preprocessing on the plurality of small orthographic satellite surveying and mapping images after real color recovery, performing image registration on the to-be-registered image and a reference image, performing image geometric correction on the registered image, and performing image mosaic processing on the plurality of images after image geometric correction to obtain a single large-scene image; and three-dimensional image matching, building mask extraction, three-dimensional building modeling and three-dimensional building post-processing are carried out on a single large scene image to obtain a three-dimensional digital surface model, and ground three-dimensional real image modeling is completed. By applying the technical scheme of the invention, the technical problem that the existing two-dimensional surveying and mapping data is difficult to meet the increasing application requirements of three-dimensional scenes is solved.

The invention discloses a sonar image geometric correction method based on image optimization, and relates to the technical field of underwater sonar imaging, and the method comprises the steps: collecting a multi-source underwater observation data packet including sonar image original data, platform motion state data and underwater environment data, and carrying out the preprocessing; extracting sonar image original data from the multi-source underwater observation data packet, performing geometric coarse correction to obtain a pre-corrected sonar image, and performing motion compensation on the obtained pre-corrected sonar image to generate a motion corrected sonar image; constructing a joint optimization objective function, carrying out geometric fine tuning on the motion correction sonar image by adopting a sliding time window strategy, and outputting a geometric fine correction sonar image; geometric distortion caused by non-uniform motion of a platform, attitude disturbance and acoustic propagation distortion is effectively eliminated, inter-frame consistency and submarine topography continuity of sonar images are remarkably improved, and the method is suitable for high-precision operation scenes such as underwater surveying and mapping, target recognition and three-dimensional reconstruction.

This invention discloses a method for estimating sea state levels based on visual information. The method includes acquiring image and video data of a target sea area through an image acquisition module; using a combination of median filtering and Gaussian filtering for noise reduction, and histogram equalization to enhance data contrast; performing image geometric correction using radial distortion correction and tangential distortion correction models; extracting wave texture features, motion features, and wave height features from the preprocessed data; inputting the extracted features into a trained sea state level classification model for training, and outputting the sea state level estimation result. During training, multi-model fusion and dynamic model updating methods are used to improve the accuracy and reliability of the estimation. This invention uses a camera to collect wave information within a certain distance and range, and automatically estimates the sea state level based on this information, thus solving the problems of high cost, limited measurement range, significant environmental influence, and low accuracy in existing sea state level estimation methods.

This invention provides a geometric correction method for high-orbit staring SAR based on multi-angle weighted image simulation in mountainous areas. The method involves selecting a DEM image D for the corresponding region; determining the coordinates of the four corner points of image D; calculating the corresponding simulated image value for each pixel in image D; performing multi-scale decomposition on each SAR multi-angle image using a non-downsampling pyramid to obtain high-frequency and low-frequency sub-bands for each image; fusing the high-frequency and low-frequency sub-bands using Gaussian blur; calculating the fusion coefficients of the high-frequency and low-frequency sub-bands; and then determining the grayscale value of the fused image; finally, matching the simulated image with the SAR image using the SIFT algorithm to obtain the geometrically corrected image. This invention effectively alleviates the problem of the significant impact of elevation on the geometric correction accuracy of images during high-orbit SAR imaging in mountainous areas.

This invention belongs to the field of digital image processing and computer vision technology, and relates to a method and related equipment for geometric correction of document images. The method includes: preprocessing a distorted document image to extract document regions from the image; using a deep learning model to extract geometric features from the document regions, obtaining structural feature lines and local angular distortion information in the image; representing the local angular distortion information as a Beltrami coefficient field, and constructing a geometric constraint model based on the structural feature lines and the Beltrami coefficient field; obtaining a quasi-conformal mapping by solving the Beltrami equation according to the geometric constraint model, and mapping the distorted image domain to a standard plane image domain based on the quasi-conformal mapping, thereby obtaining the corrected document image. This invention extracts macroscopic structural feature lines and microscopic local distortion information through a deep learning model, and combines this with quasi-conformal mapping theory to construct a geometric constraint model, which can maintain the consistency of local character shapes while correcting the overall structure of the document image, effectively improving the quality of geometric restoration of the document image.

The application discloses a kind of underwater binocular three-dimensional reconstruction methods based on refraction geometry modeling and adaptive matching, belong to the technical field of underwater three-dimensional reconstruction, including: constructing refraction equivalent pinhole model, parameter calibration and image geometry correction are carried out;Adaptive enhancement underwater binocular image;Construct image quality joint evaluation index;And pixel-level fusion is carried out to two parallax maps, and fusion parallax map is obtained;Adaptive three-dimensional reconstruction is carried out to fusion parallax map.The method of the present application starts from physical imaging model, and sequentially designs three links of geometry correction, adaptive enhancement, adaptive cost aggregation, and the metric generated in the previous link will directly enter the next link to participate in weight design and optimization, in this way, imaging geometry, image observation and matching algorithm are no longer independent black boxes, but are synergistically optimized around the goal of "obtaining stable and reliable parallax map in underwater environment and completing high-precision three-dimensional reconstruction".

The invention relates to the technical field of computer vision and remote sensing image processing, and discloses an underwater hyperspectral push-broom image geometric correction method. The method comprises the following steps: deploying an underwater push-broom platform with adjustable supporting legs, sensing a local terrain by using an acoustic ranging array and automatically leveling to ensure that the optical axis of a hyperspectral imager is vertical to the seabed; synchronously fusing the inertial measurement unit, the depth sensor and acoustic ranging data to generate a six-degree-of-freedom pose time sequence; spatial inversion and affine transformation resampling are carried out on line-by-line spectral images based on the sequence, a hyperspectral data cube after geometric correction is generated through splicing, and radiation cosine correction driven by attitude angles is supplemented. The method improves the space consistency and radiation precision of the underwater hyperspectral image, and is suitable for the fine detection of a complex seabed environment.

The invention provides a kind of space measurement and image correction method based on laser positioning.The method includes laser projection and image acquisition,light spot identification and coordinate extraction,space coordinate calculation,plane fitting and coordinate correction,perspective transformation and pixel calibration and image geometric correction and other steps.The method establishes a reliable benchmark for geometric correction based on the space coordinates of the positioning points.Through multi-point plane fitting and coordinate projection correction,the influence of perspective distortion and measurement error is effectively eliminated.The innovative perspective transformation matrix calculation method combined with geometric constraint optimization ensures the accuracy and stability of image correction.The established pixel equivalent calculation model realizes the accurate conversion from pixel size to physical size,providing a reliable guarantee for subsequent accurate measurement.

The invention provides an image virtual level calibration method and system for a power monitoring deploy and control ball, and relates to the technical field of image geometric correction. Collecting real-time acceleration data, calculating an inclination angle, calculating an inclination angle variance in a sliding window, and forcibly multiplexing an image geometric correction matrix cached at the previous moment if the variance exceeds the standard; otherwise, further combining the angle change micro-motion threshold value of the inclination angle and the cache maximum effective duration to carry out dual verification, reconstructing the image geometric correction matrix only when the inclination angle change exceeds the micro-motion threshold value or the cache duration exceeds the maximum effective duration, otherwise, continuing to multiplex the cached image geometric correction matrix, and finally, reusing the cached image geometric correction matrix when the inclination angle change exceeds the micro-motion threshold value or the cache duration exceeds the maximum effective duration. And converting a video image currently acquired by the power monitoring deploy and control ball to obtain a virtual horizontal view angle image after horizontal calibration. According to the scheme, the accumulated error generated by long-time operation of the power monitoring deploy and control ball is eliminated while the computing power consumption of the embedded processor is greatly reduced, and the quality of the finally acquired image is improved.

The application discloses a kind of crack real-time detection method and device based on coin reference, the method is collected by smart phone crack image containing standard size coin, through coin detection, perspective transformation, crack analysis realizes accurate crack quantitative measurement.Main technical scheme includes:1) coin detection module, the position of reference coin, profile is accurately identified by improved ellipse detection algorithm combined with hand region shielding technology;2) perspective transformation module, based on coin position, image geometry correction is realized using perspective transformation;3) crack analysis module, "you only look once" algorithm YOLO (You Only Look Once) and skeletonization algorithm are used to realize sub-millimeter crack measurement.The application first proposes nondestructive testing scheme of smart phone combined with coin reference object, while ensuring measurement accuracy, significantly reduces hardware cost, and the detection accuracy can reach ±0.2mm, suitable for civil engineering detection and identification and other fields.

This invention provides a deformation measurement method and system based on feature matching and two-stage image correction. The core of this deformation measurement method lies in employing a two-stage image geometric correction mechanism: First, based on SURF feature matching, an affine transformation matrix is ​​calculated to perform preliminary correction on deformed images exhibiting large-angle rigid body motion, eliminating in-plane rotation and translation. Then, based on SURF feature matching again, a projection transformation matrix is ​​calculated to perform fine correction on the pre-corrected image, compensating for perspective distortion caused by the camera optical axis not being perpendicular to the plane of the measured object. Finally, digital image correlation calculations are performed on the corrected image to obtain an accurate full-field deformation field. The deformation measurement system includes an image acquisition unit, an image processing unit, and an output unit. This invention fundamentally solves the measurement failure problem caused by geometric miscorrelation and speckle miscorrelation in traditional two-dimensional digital image correlation technology under large-angle rotation or camera motion.

The invention relates to the technical field of computer vision and aided driving, in particular to a dynamic inverse perspective transformation delay compensation method based on IMU (Inertial Measurement Unit) grey prediction. And attitude synchronization and image geometric correction of a vehicle-mounted camera in a vehicle movement process are realized by combining dynamic inverse perspective transformation, so that the accuracy and stability of aerial view generation of an automatic driving system in a dynamic scene can be improved, and the problem that image frames are mismatched with vehicle attitude information due to sensor data delay in the prior art is solved. And therefore, an inverse perspective transformation result is distorted, and a subsequent perception decision is influenced.