A hand-held or otherwise portable or spatial or temporal performance-based image capture device includes one or more lenses, an aperture and a main sensor for capturing an original main image. A secondary sensor and optical system are for capturing a reference image that has temporal and spatial overlap with the original image. The device performs an image processing method including capturing the main image with the main sensor and the reference image with the secondary sensor, and utilizing information from the reference image to enhance the main image. The main and secondary sensors are contained together within a housing.

A method of structural masking for progressive health monitoring of a structural component includes receiving a current image of the structural component. A processor aligns the current image and a reference image of the structural component. The processor performs a structure estimation on the current image and the reference image to produce a current structure estimate image and a reference structure estimate image. The processor generates a structural mask from the reference structure estimate image. The processor masks the current structure estimate image with the structural mask to identify one or more health monitoring analysis regions including a potential defect or damaged area appearing in the masked current structure estimate image that does not appear in the reference structure estimate image.

Implementations of the present disclosure include receiving a training image, providing a hash pattern that is representative of the training image, applying a plurality of filters to the training image to provide a respective plurality of filtered training images, identifying a filter to be associated with the hash pattern based on the plurality of filtered training images, and storing a mapping of the filter to the hash pattern within a set of mapping in a data store.

The subject disclosure presents systems and methods for automatically selecting meaningful regions on a whole-slide image and performing quality control on the resulting collection of FOVs. Density maps may be generated quantifying the local density of detection results. The heat maps as well as combinations of maps (such as a local sum, ratio, etc.) may be provided as input into an automated FOV selection operation. The selection operation may select regions of each heat map that represent extreme and average representative regions, based on one or more rules. One or more rules may be defined in order to generate the list of candidate FOVs. The rules may generally be formulated such that FOVs chosen for quality control are the ones that require the most scrutiny and will benefit the most from an assessment by an expert observer.

The invention relates to technologies for visualizing a three-dimensional (3D) image. According to the claimed method, a 3D model is generated, images of an object are produced, a 3D model is visualized, the 3D model together with a reference pattern and also coordinates of texturing portions corresponding to polygons of the 3D model are stored in a depiction device, at least one frame of the image of the object is produced, the object in the frame is identified on the basis of the reference pattern, a matrix of conversion of photo image coordinates into dedicated coordinates is generated, elements of the 3D model are coloured in the colours of the corresponding elements of the image by generating a texture of the image sensing area using the coordinate conversion matrix and data interpolation, with subsequent designation of the texture of the 3D model.

Disclosed is an image quality evaluation method for a digital pathology system according to the present invention. The image quality evaluation method includes receiving a digital slide image by an image quality evaluation unit; dividing the digital slide image into a plurality of blocks by the image quality evaluation unit; analyzing the plurality of blocks to extract a foreground; calculating a blur for the extracted foreground; calculating brightness distortion for the extracted foreground; calculating contrast distortion for the extracted foreground; and evaluating the overall quality of the digital slide image using the blur, the brightness distortion, and the contrast distortion by the image quality evaluation unit.

A workpiece inspection device 1 includes a table (3), image capturing unit fixing part (7), first light projection unit (4), second light projection unit (5), linear movement mechanism (8), turning mechanism (9), quality determination unit (10), and control unit (11). The control unit (11) performs first image capturing step of causing first light projection unit (4) to project light and causing image capturing unit (6) to capture image, detailed inspection portion-determination step of setting, portion of workpiece (2) determined to require detailed inspection based on image captured in the first image capturing step, second image capturing step of causing second light projection unit (5) to project light onto the workpiece (2) and causing image capturing unit (6) to capture image of the detailed inspection-requiring portion, and quality determination step of determining quality of the detailed inspection-requiring portion based on image captured in the second image capturing step.

Various embodiments of the present technology generally relate to unmanned aerial vehicle (UAV) scale rendered analysis, orthomosaic, and 3D mapping and landing platform systems. More specifically, some embodiments relate to systems, methods, and means for the collection and processing of images captured during a UAV flight sequence. In some embodiments, the UAV landing platform retrieves flight information and initial map information over a unidirectional virtual private network from a multitenant cloud-based scheduling application. The UAV landing platform sends the initial map information to a UAV over a WiFi, Bluetooth, or radio frequency network and initiates a drone flight sequence once the drone flight sequence has been approved by a local user. The UAV landing platform receives property image data from a UAV after a UAV flight sequence has ended and transmits the received property image data back to the cloud application.

An image processing apparatus includes a first evaluator configured to evaluate under a first evaluation condition a focus state of each of a plurality of image data acquired by consecutive capturing, a second evaluator configured to evaluate the focus state of each of the plurality of image data under a second evaluation condition different from the first evaluation condition, and a recorder configured to record first evaluation information indicating an evaluation result under the first evaluation condition and second evaluation information indicating an evaluation result under the second evaluation condition.

A remote sensing image geometric normalization method and apparatus. The method comprises: constructing a pyramid tile structure for a reference image, and releasing reference tile data, wherein the reference tile data is data in the pyramid tile structure (S11); according to the resolution and geographic coordinates of an image to be subjected to geometric normalization, calculating the level of a tile to be downloaded and the name of the tile to be downloaded, and according to the level of the tile to be downloaded and the name of the tile to be downloaded, downloading corresponding data from the reference tile data to obtain a standard tile set (S12); performing first geometric correction on the image to be subjected to geometric normalization and tiles in the standard tile set to obtain a first image processing result (S13); matching the first image processing result with the tiles in the standard tile set to obtain a plurality of control points, and using the plurality of control points to calculate a result evaluation precision (S14); and according to the result evaluation precision, determining whether to perform second geometric correction on the first image processing result (S15). The method improves the efficiency of processing a remote sensing image.