A method, device, computer system and computer readable storage medium for 3D reconstruction are provided. The method comprises: performing a 3D reconstruction of an original 2D image of a target object to generate an original 3D object corresponding to the original 2D image; selecting a complementary view of the target object from candidate views based on a reconstruction quality of the original 3D object at the candidate views; obtaining a complementary 2D image of the target object based on the complementary view; performing a 3D reconstruction of the complementary 2D image to generate a complementary 3D object corresponding to the complementary 2D image; and fusing the original 3D object and the complementary 3D object to obtain a 3D reconstruction result of the target object.

An image processing method is provided. For each frame of a video stream, a pixel digital frame mask in the respective frame of the video stream is obtained. The pixel digital frame mask of the respective frame includes a plurality of preset pixel position sets. At least two target preset pixel position sets are determined from the plurality of preset pixel position sets that form a frame sequence number of the respective frame based on values of pixels included in the at least two target preset pixel position sets. A frame sequence number corresponding to the respective frame of the video stream is determined according to positions of the at least two target preset pixel position sets in the pixel digital frame mask in the respective frame. Further, video fluency of the video stream is determined based on the frame sequence numbers.

Multispectral imaging and related techniques are provided to detect thermal and non-thermal anomalies at reduced false detection rates. A multispectral imaging system includes an infrared light imaging sensor that captures infrared image data in a first spectral band, of a scene and an ultraviolet light imaging sensor that captures ultraviolet image data in a second spectral band, of the scene. The system also includes a processor that combines the ultraviolet image data and the infrared image data to generate composite image data, determines a ratio of a first radiant intensity in the first spectral band to a second radiant intensity in the second spectral band, from the composite image data, and determines whether the ratio corresponds to a predetermined radiant intensity ratio of a known thermal or electrical anomaly. The processor can detect the thermal or electrical anomaly when the determined ratio corresponds to the predetermined radiant intensity ratio.

The present disclosure provides an electronic apparatus capable of capturing an image without being affected by an abnormality on a display surface.

The electronic apparatus includes: a display unit; an imaging unit that is disposed on an opposite side to a display surface of the display unit; an abnormality detection unit that detects an abnormality on the display surface; and a display control unit that highlights a position where the abnormality detected by the abnormality detection unit occurs on the display unit.

A computer-implemented method is provided for improving live video quality. The method comprises: acquiring, using a medical imaging apparatus, a stream of consecutive image frames of a subject, and the stream of consecutive image frames are acquired with reduced amount of radiation dose; applying a deep learning network model to the stream of consecutive image frames to generate an image frame with improved quality; and displaying the image frame with improved quality in real-time on a display.

A process includes: (i) receiving image data, dividing a portion of the image data into a plurality of grids including a first grid, a second grid, a third grid, and a fourth grid, dividing the portion of the image data into a plurality of areas including (a) a first area including the first grid and the third grid, and (b) a second area including the second grid and the fourth grid; (ii) detecting an object relating to the first grid; and (iii) when the object is detected in the first grid, generating a signal for controlling discharge of fluid from a fluid discharging unit so that fluid flows through the first area including the first grid.

Some example embodiments relate to a super resolution scanning electron microscope (SEM) image implementing device and/or a method thereof. Provided a super resolution scanning electron microscope (SEM) image implementing device comprising a processor configured to crop a low resolution SEM image to generate a first cropped image and a second cropped image, to upscale the first cropped image and the second cropped image to generate a first upscaled image and a second upscaled image, and to cancel noise from the first upscaled image and the second upscaled image to generate a first noise canceled image and a second noise canceled image.

Disclosed are an image processing method and apparatus, a computer device and a storage medium, which relate to the field of artificial Intelligence. The method includes receiving an original image; performing image photographing defect detection and color deviation detection on the original image, the image photographing defect detection determining whether there exists a photographing defect that is irreparable through image processing, the color deviation detection determining whether there exists color cast in the original image; performing color correction on the original image if the original image passes the image photographing defect detection and does not pass the color deviation detection; and generating a target image based on the color-corrected original image.

A computing system including a processing circuit in communication with a camera having a field of view. The processing circuit is configured to perform operations related to detecting, identifying, and retrieving objects disposed amongst a plurality of objects. The processing circuit may be configured to perform operations related to object recognition template generation, feature generation, hypothesis generation, hypothesis refinement, and hypothesis validation.

Disclosed are a system and a method for ultrasound elastography and a method for dynamically processing frames in real time. The system includes an elasticity processing apparatus having an elasticity information detecting module for extracting elasticity information representing the elasticity of a target to be detected; a quality parameter calculating module for calculating at least a quality parameter reflecting quality of each elasticity image corresponding to the elasticity information; and a frame processing module for determining whether to output corresponding elasticity image based on the quality parameter of each elasticity image. When calculating a strain of consecutive images, the parameter reflecting the quality of each image is also computed, through which, the current elasticity image is determined whether to be displayed, thus avoiding the situation that colors of acquired successive elasticity images may vary greatly due to large difference existing in stress.