149 results about "Aerial imaging" patented technology

Methods and systems for inspecting a reticle are provided. In an embodiment, a method may include forming an aerial image of the reticle using a set of exposure conditions. The reticle may include optical proximity correction (OPC) features. The method may also include detecting defects on the reticle by comparing the aerial image to a reference image stored in a database. The reference image may be substantially optically equivalent to an image of the reticle that would be printed on a specimen by an exposure system under the set of exposure conditions. The reference image may not include images of the OPC features. Therefore, a substantial portion of the defects include defects that would be printed onto the specimen by the exposure system using the reticle under the set of exposure conditions. The method may also include indicating the defects that are detected in critical regions of the reticle.

Methods and systems for inspecting a reticle are provided. A method may include forming an aerial image of the reticle with an inspection system at a wavelength different from a wavelength of an exposure system. The method may also include correcting the aerial image for differences between modulation transfer functions (MTF) of the inspection system and the exposure system. In this manner, the corrected aerial image may be substantially equivalent to an image of the reticle that would be printed onto a specimen by the exposure system at the wavelength of the exposure system. In addition, the method may include detecting defects on the reticle using the corrected aerial image. The detected defects may include approximately all of the defects that would be printed onto a specimen by the exposure system using the reticle.

A reticle inspection system for inspecting reticles can be used as an incoming inspection tool, and as a periodic and pre-exposure inspection tool. Mask shops can use it as an inspection tool compatible to their customers, and as a printable error detection tool. The inventive system detects two kinds of defects: (1) line width errors in the printed image; (2) surface defects. The line width errors are detected on the die area. The detection is performed by acquiring the image of the reticle under the same optical conditions as the exposure conditions, (i.e. wavelength, numerical aperture, sigma, and illumination aperture type) and by comparing multiple dies to find errors in the line width. Surface defects are detected all over the reticle. The detection of surface defects is performed by acquiring transmission and dark-field reflection images of the reticle and using the combined information to detect particles, and other surface defects.

The invention provides an automatic registration method of an airborne laser point cloud and an aerial image. The automatic registration method comprises the following steps of: extracting a building outline from the point cloud without interpolation for the laser point cloud; obtaining building angular characteristics as a registration element through outline regularization; automatically matching the point cloud with the image according to the homonymic angular characteristics with the aid of an approximate exterior orientation element of the aerial image; and utilizing bundle block adjustment and a cyclic iterative policy so as to realize overall optimal registration of aerial image and point cloud data. The registration method provided by the invention has the following advantages that: the building outline is directly extracted from the laser point cloud without interpolation for the laser point cloud so as to obtain the building angular characteristics as the registration element, which prevents interpolation errors and improves the registration accuracy; and the exterior orientation element of the image is solved by virtue of bundle block adjustment, and meanwhile overall optimal registration between the aerial image and the airborne laser point cloud is realized by adopting the cyclic iterative registration policy.

Disclosed is a method and system for processing images from an aerial imaging device. A moving vehicle analysis system receives images from an aerial imaging device. The system may perform edge analysis in the images to identify a pairs of edges corresponding to a road. The system may identify pixel blobs in the images including adjacent pixels matching each other based on a pixel attribute. The system uses a machine learning model for generating an output identifying moving vehicles in the images. The system determines a count of the moving vehicles captured by the images, where each moving vehicle is associated with corresponding pixel blobs.

The invention discloses a POS-aided method for matching aerial images, which comprises the following steps: firstly, utilizing an exterior orientation element obtained by the POS to construct a homonymous nucleofilament constraint equation and predict the initial parallax of an image; then, establishing an image pyramid according to the initial parallax and an approximate one-dimensional image correlation which carries out nucleofilament constraint layer by layer on the image of the pyramid; and finally adopting the matching of least-square images to confirm homonymous image points and pick mismatched points, thereby obtaining the homonymous image points of the images to be matched. The invention which adopts the POS-aided image matching method to automatically measure image points has the advantages that not only the application potential of the POS can be fully developed; but also the matching rate and the matching efficiency of automatically rotating points can be improved; and the problems that the rotating points of the images are so difficult to be matched that the rotating points are required to be measured manually and interactively are solved, for example, the rotational angles of certain images are too large, the image texture is not obvious, and the topographic relief is bigger.

Disclosed is a method for automatically extracting and locating power lines based on an unmanned aerial vehicle image. The method comprises the steps that an unmanned aerial vehicle is used for double-air-strip flight to obtain an aerial image; the power lines of the aerial image are automatically extracted, and the aerial image is extracted through an LSD linear detection method; rough extraction is carried out through radiation features of the power lines, and background information is eliminated through connectivity; the background information with an LSD detection image removed is united, the remaining background information is eliminated, and meanwhile the detected power lines are connected; three-dimensional data of the power lines of the aerial image are located to carry out epipolar line image extraction, epipolar lines and wires intersect with one another to solve homonymy point coordinates, the forward intersection is carried out, and the three-dimensional data of the power lines are obtained. The efficiency of a three-dimensional line patrol system is improved, more precise three-dimensional coordinates are obtained, and the cost for power line corridor line patrol is lowered.

A method for reducing the effects of background radiation introduced into gaseous plume spectral data obtained by an aerial imaging sensor, includes capturing spectral data of a gaseous plume with its obscured background along a first line of observation and capturing a second image of the previously obscured background along a different line of observation. The parallax shift of the plume enables the visual access needed to capture the radiometric data emanating exclusively from the background. The images are then corresponded on a pixel-by-pixel basis to produce a mapping. An image-processing algorithm is applied to the mapped images to reducing the effects of background radiation and derive information about the content of the plume.

In a computer-implemented method, one or more digital aerial images of a property of a current or potential policyholder may be received. The digital aerial image(s) (e.g., camera images, spectrometer images, LiDAR images, etc.) may be processed according to one or more image analysis techniques to determine one or more features of the property. The property feature(s) (e.g., tree heights, distances between trees and homes, sizes and/or masses of tree limbs, presence of ice dams, etc.) may be analyzed to determine a risk of damage to a structure or object located on the property. Based on the risk of damage, a risk output that includes (i) an indication of whether action should be taken to mitigate the risk of damage, (ii) an indication of whether insurance coverage associated with the structure or object should be offered, and/or (iii) a measure of the risk of damage, may be generated.

Reticles may comprise shading elements (SEs) for locally altering the reticle optical properties. However, such reticles may degrade over time as a result of repeated exposure to radiation in a lithography process, as the radiation may “heal” the SEs. Disclosed are techniques for monitoring a reticle in order to maintain confidence about the reticle's optical properties and the uniformity of patterns on wafers that are to be printed using the reticle. Reticles undergo periodic inspection comprising reticle transmission measurement and/or aerial imaging of the reticle. When such inspection indicates sufficient reticle degradation, the reticle is tagged for correction prior to its subsequent use in a lithography process.

The invention relates to a measurement device and method based on laser distance measurement and object space matching virtual control points, and relates to the field of aerial triangle surveying and mapping of unmanned aerial vehicles. Including data acquisition, feature point extraction and matching, digital surface model generation, matching point probabilistic object coordinate acquisition, refined matching results, correction of external elements, calculation of ground coordinates, etc. The UAV is also equipped with a surveying and mapping device, including obtaining Aerial cameras for aerial images, long-range laser rangefinders for obtaining point cloud data, and airborne positioning devices for obtaining approximate outer orientation elements and instantaneous time stamp data of aerial cameras. Realize accurate surveying and mapping of ground objects.

A camera triggering and aerial imaging mission visualization system. More specifically, a system that controls camera triggering, manages data from a positioning system and an attitude measuring device, and provides real-time image coverage and mission visualization in manned and unmanned aerial imaging applications. The system includes a control and data management device that interfaces with at least one camera; one or more positioning systems; one or more attitude measuring devices; one or more data transmission devices; and a mission visualization system. The aerial imaging system may be interfaced with a variety of commercial, off-the-shelf or custom cameras for use in aerial imaging on manned and unmanned aircrafts, and may also be used on other types of vehicles or for other applications.

The invention discloses a building shielding detection and shielding area compensation method by use of ghost images. The method comprises the following steps: 1, performing secondary utilization on a result (ghost images) of conventional ortho-rectification; 2, performing shielding compensation by use of such a feature that ghost images are not geometrically deformed; and 3, performing shielding detection completely on buildings in aerial images, detecting ghost roofs (roofs obtained through the ortho-rectification) of the buildings in the ghost images and projection roofs by use of DBM, and by use of relations between the ghost images and shielding areas, determining that pixel areas occupied besides the roof portions of the buildings in the ghost images are the shielding areas. According to the invention, shielding detection is carried out by use of the method, and he problems of fake shielding and fake visibility existing in a conventional shielding detection method are eliminated. In the detection process, the building roofs in the whole images are firstly extracted, then gray processing is performed on the shielding areas, and the problem of coverage of the shielding areas when a part of the building roofs are re-detected after detection is avoided. The operation is simple, the shielding detection speed is improved, and the detection cost is decreased.

The invention provides an image restoration method based on an aerial TDI-CCD (Time Delay and Integration-Charge Coupled Device) imaging error vibration model. In the method, vibration frequencies are classified into low-frequency vibration and high-frequency vibration without regard to high-frequency vibration; the low-frequency vibration is taken as random vibration, and a low-frequency vibration model is established; the low-frequency vibration is decomposed into displacements in three direction of X, Y and Z on the basis of the low-frequency vibration model, and displacement expressions in the directions X, Y and Z are established; the high-frequency vibration is taken as the simple harmonic vibration of a set frequency in a set direction, and a high-frequency vibration model is established; and imaging errors generated by displacement changes caused by the low-frequency vibration in each direction are respectively corrected by adopting different image restoration algorithms in each direction when software image restoration is carried out. The method can more reasonably simulate the actual situation of aerial imaging, and the models established by the invention can improve the precision of the TDI-CCD image restoration.

The embodiment of the present invention discloses a transflective film and an aerial display device. The aerial display device comprises: a first polarizing device and a second polarizing device disposed on a box; and a transflective structure and a transflective film disposed between the first polarizing device and the second polarizing device. The aerial display device is provided with a first quarter-wavelength plate at a side close to the first polarizing device. A second quarter-wavelength plate is disposed between the transflective structure and the transflective film. According to the aerial display device, the polarized light passing through the first polarizing device is processed by an optical path inside the aerial display device such that the polarized light passing through thesecond polarizing device forms an aerial image. The embodiment of the present invention solves the problems in the existing aerial imaging technology that a display device is large in size, complicated in structure, simple in displayed images, and poor in display effect, and has difficulty in displaying three-dimensional images.

The invention discloses an unmanned aerial vehicle image building roof extraction method based on a full convolutional neural network. The method comprises the following steps: in a first part, establishing an aerial image building roof sample library; in the second part, designing a full convolutional neural network to carry out feature learning on a building roof sample; performing building roofdetection by using the trained network, and obtaining a more accurate building roof result through post-processing of an extraction result in a third part. The method is different from a traditionalextraction method, and makes full use of rich unmanned aerial vehicle image resources in the aspect of data acquisition. In an algorithm design aspect, a specific full convolutional neural network based on skip layer connection is designed, gradient diffusion and gradient explosion are prevented while building roof features are fully extracted. In the aspect of post-processing, a conditional random field and a D-S evidence theory are utilized to carry out building roof extraction result post-processing, and the extraction precision of the unmanned aerial vehicle image building roof is improvedthrough post-processing.

The invention discloses a real-time photogrammetry processing system of an airborne aerial image. The real-time photogrammetry processing system comprises a data transmission and control board and three data processing boards, wherein a camera and a POS (Point Of Sale) system are used for respectively obtaining data; the data transmission and control board is used for receiving the data obtained by the camera and the POS system and respectively sending the received data to the three data processing boards; the three data processing boards are used for respectively carrying out image colour quality evaluation, image geometric quality evaluation and panoramic image mosaic processing; and a processing result is stored in a hard disk and displayed on a display. With regard to airborne photogrammetry real-time processing, the real-time photogrammetry processing system disclosed by the invention has a clear goal and a more fixed data processing content; the airborne photogrammetry real-timeprocessing is realized by adopting an embedded system orienting to special application; the real-time photogrammetry processing system has strong advantages, such as small system volume, low power consumption and high processing speed; and the real-time photogrammetry processing system is convenient to install on a machine.

Novel automatic aero-triangulation software is disclosed. With wide application of unmanned aerial vehicles, responses to emergencies can be carried out by means of the unmanned aerial vehicles as a platform to perform photogrammetry. The software aims to aerial images, especially to aerial image treatment in the unmanned aerial vehicles. In the software, a feature extraction algorithm of large data is employed for treating the aerial images and a block adjustment of the large data is treated in a manner of internal and external memories, and meanwhile camera parameters are calculated.

The invention discloses a method for monitoring a farmland cotton aphid damage grade model based on unmanned aerial vehicle imaging. The method comprises the following steps: 1) performing data acquisition; 2) performing data preprocessing; 3) performing regression analysis; and 4) constructing a model; wherein the data acquisition comprises unmanned aerial vehicle aerial imaging hyperspectral data acquisition and ground non-imaging hyperspectral data acquisition; establishing a cotton canopy leaf area index LAI hyperspectral remote sensing estimation model corresponding to different aphid damage levels according to the farmland acquisition data, and performing inversion by applying an imaging hyperspectral image to obtain a visual and quantitative cotton canopy leaf area index LAI spatialdistribution map. A hyperspectral instrument is combined with an unmanned aerial vehicle technology, and according to an electromagnetic wave theory, electromagnetic wave information radiated and reflected by different sensors to a target is applied to perform data acquisition and processing on a farmland, and finally imaging is performed to construct a hyperspectral remote sensing cotton aphid occurrence situation identification model.

The invention relates to the field of optical imaging, especially an aerial imaging element, an aerial imaging display device, and an application of the aerial imaging display device. In order to solve the above problems, the invention provides an optical element which is simple in structure, is low in production cost, and is suitable for a large-scale aerial imaging display platform. The invention discloses an optical element which enables the light of an incident image to be bent. The bottom section of the optical element is a spherical reflection surface, and the light forms an aerial image corresponding to the incident image after the light is reflected by the reflection surface of the bottom of the optical element at least two times. The application of the aerial imaging technology does not need any medium, and can achieve a real image in the sky without any real object. A person can touch the image through a finger, and also can operate the aerial image, thereby achieving a novel aerial imaging robot interaction system.