4 results about "Pattern space" patented technology

This invention provides a method, apparatus, device, and medium for pattern defect detection and repair. The method includes: preprocessing an input image to obtain a preprocessed image; extracting pattern units from the preprocessed image and calculating parameters for characterizing the pattern space and feature patterns; detecting and locating defects based on the feature vector of the standard unit and the average adjacent spacing; generating a repaired image block; and fusing the repaired image block with the original image. The aim is to completely solve the core pain points of traditional methods, such as strong reliance on manual intervention, high defect miss rate, poor repair effect, and weak scene adaptability.

An image encoding / decoding method, a bitstream transmission method, and a computer-readable recording medium storing a bitstream are provided. An image decoding method according to the present disclosure may be an image decoding method performed by an image decoding apparatus, comprising: constructing candidates for a spatial geometric partition mode (spatial geometric partition mode, SGPM), wherein each of the candidates includes a prediction mode for an intra prediction mode of each partition divided by a partition mode of the SGPM; and predicting a current block based on one of the candidates, wherein a prediction mode of a first candidate among the candidates is determined as information indicating an intra block copy prediction mode of a reference position.

This invention discloses a method for rapidly reconstructing the electromagnetic characteristics of an unmanned aerial vehicle (UAV) swarm with variable attitude. The method treats each UAV in the swarm as an independently reusable electromagnetic module, constructing its spherical multi-port response model through a single full-wave simulation. It utilizes analytical spherical propagation operators to describe the free-space electromagnetic coupling between UAVs, and analytically characterizes the impact of UAV attitude and position changes on radiation patterns using spherical geometric transformation and translation operators. After assembling the swarm-level linear system in the spherical pattern space, the radiation and scattering electromagnetic characteristics of the UAV swarm under arbitrary attitude and formation conditions can be rapidly reconstructed without re-performing a full-wave simulation.