4results about How to "Downsampling" patented technology

The application belongs to the technical field of radar signal processing and imaging, and provides a differential coupling single-frequency time-varying low-quantization imaging method, which comprises receiving a SAR echo signal, constructing a single-frequency time-varying threshold signal, single-bit quantization processing of a reference channel, single-bit quantization processing of a phase shift channel, double-channel data fusion and harmonic cancellation, and imaging processing based on a synthesized signal. The application effectively reduces the quantization noise base and improves the detection capability of a SAR system on weak targets under the premise of not significantly increasing the hardware cost.

The embodiment of the invention discloses an image rendering method and device and electronic equipment. The method comprises the steps that an image picture collected by a target camera is written into a target rendering texture; obtaining a width value and a height value of the target rendering texture in a three-dimensional space according to the resolution of the target rendering texture, the pixel ratio per unit and the zoom factor; constructing a cylinder model according to the width value and the height value of the target rendering texture in the three-dimensional space, and obtaining the horizontal resolution and the vertical resolution corresponding to the cylinder model; constructing a three-dimensional grid according to the horizontal resolution and the vertical resolution corresponding to the cylinder model; performing image rendering on the three-dimensional grid according to textures in the target rendering textures; according to the method, scene rendering is performed in combination with the rendering texture, and scene content does not need to be drawn on a buffer, so that one-time additional texture sampling is reduced, the whole rendering process is simplified, and meanwhile, the rendering quality can be improved.

The invention discloses a terahertz hyperspectral image recovery method and system based on low-rank joint sparsity, and mainly solves the problems that in the prior art, a terahertz hyperspectral image recovery method adopts a single primary function for representation, detail loss and artifacts are easily caused, and the imaging quality is poor in a low sampling rate or low signal-to-noise ratio environment. According to the implementation scheme, the method comprises the following steps: sparsely acquiring a terahertz hyperspectral image of an image domain to obtain actual observation data; defining a sparse forward transformation operator and a sparse inverse transformation operator by using multiple groups of wavelet bases and Dirac bases; the method comprises the following steps: constructing a terahertz hyperspectral image recovery model based on low-rank joint sparse constraint by using actual observation data and a sparse forward transformation operator, and solving the image recovery model by using a primal-dual splitting method to obtain a recovered terahertz hyperspectral image. The terahertz hyperspectral image recovery method realizes high-resolution terahertz hyperspectral image recovery in an extremely low sampling rate or low signal-to-noise ratio environment, and can be used for medical auxiliary diagnosis, security check screening and drug detection.

The invention discloses a low-power-consumption geomagnetic vehicle detection method and system. The method comprises the following steps: acquiring triaxial geomagnetic data; performing first-order difference and filtering on the three-axis data to obtain a smooth first-order difference signal; in a vehicle-free state, a mean value and a standard deviation are obtained through calibration, a Gaussian probability density function is established, an integral interval is constructed based on a deviation amount, a single-axis condition probability item is calculated through integration, and three-axis fusion is performed in combination with a state-related correlation correction coefficient to obtain a vehicle existence probability; in a state machine model including no vehicle, arrival detection, delay confirmation, and vehicle passing and leaving detection, outputting a vehicle arrival moment and a vehicle leaving moment according to a vehicle existence probability, a hysteresis threshold, a continuous point criterion and a delay confirmation mechanism, and compensating and correcting group delay introduced by filtering; and reporting detection information when the vehicle arrival event or departure event is output. According to the method, low power consumption and baseline drift resistance are both considered under the condition of a relatively low sampling rate, and the vehicle detection robustness is improved.