159 results about "Weighting filter" patented technology

A first aspect of the present invention relates to a method for low-frequency emphasizing the spectrum of a sound signal transformed in a frequency domain and comprising transform coefficients grouped in a number of blocks, in which a maximum energy for one block is calculated and a position index of the block with maximum energy is determined, a factor is calculated for each block having a position index smaller than the position index of the block with maximum energy the calculated maximum energy and the energy of the block, and, for each block, a gain determining from the factor is applied to the transform coefficients of the block. Another aspect of the invention is concerned with an HF coding method for coding, through a bandwidth extension scheme, an HF signal obtained from separation of a full-bandwidth sound signal into the HF signal and a LF signal, in which an estimation of the an HF gain is calculated from LPC coefficients, the energy of the HF signal is calculated, the LF signal is processed to produce a synthesized version of the HF signal, the energy of the synthesized version of the HF signal is calculated, a ratio between the energy of the HF signal and the energy of the synthesized version of the HF signal is calculated and expressing as an HF gain, and a difference between the estimation of the HF gain and the HF gain is calculated to obtain a gain correction. A third aspect of the invention is concerned with a method for producing from a decoded target signal an overlap-add target signal in a current frame coded according to a first coding mode. According to this method, the decoded target signal of the current frame is windowed and a left portion of the window is skipped. A zero-input response of a weighting filter of the previous frame coded according to a second coding mode is calculated and windowed so that the zero-input response has an amplitude monotonically decreasing to zero after a predetermined time period. Finally, the calculated zero-input response is added to the decoded target signal to reconstruct the overlap-add target signal.

The invention belongs to the field of infrared image processing, and mainly relates to an infrared weak and small target detection method based on time-space domain background suppression. The infrared weak and small target detection method is used for achieving the aim of infrared movement weak and small target detection in a complicated background and includes the steps that firstly, stable background noise waves in a space domain are suppressed through guiding filtering; secondly, slowly-changed backgrounds in a time domain are suppressed with a gradient weight filtering method on the time domain through target movement information in an infrared image sequence; thirdly, the time domain background suppression result and the space domain background suppression result are fused to obtain a background-suppressed weak and small target image; finally, the image is split through a self-adaptation threshold value, and a weak and small target is detected. By means of the infrared weak and small target detection method, during target detection, space grey information of the infrared weak and small target is used, time domain movement information of the target is further sufficiently used, the background noise waves are suppressed in the time domain and the space domain, and therefore the movement weak and small target detection performance in the complex background is greatly improved.

A system and method for locating optimal routes between source and destination nodes in a communications network, in particular, a wireless ad-hoc communications network by employing a link reliability algorithm that estimates the reliability of links between nodes using a prediction mechanism and a variable-weight filter. The prediction can be based on signal strength, signal-to-noise ratio or any statistic collected at the physical layer that is deemed representative of the quality of a link, and the weighting filter adjusts the predicted value based on the traffic conditions (e.g., idle, light traffic, moderate traffic or heavy traffic) being experienced by the nodes whose link quality is being estimated.

In a method of recovering timing information over packet networks, a receiver receives a plurality of packet streams over different paths from the same source. The raw delays experienced by the timing packets for each stream are filtered to provide a filtered delay for each stream. The filtered delays are weighted based on the quality of each stream, and the weighted filtered delays are then combined to form an aggregate delay estimate. Frequency adjustments for a local clock at the receiver are derived from the aggregate delay estimate.

The invention provides a method for testing the insulation resistance of a vehicle body, comprising the following steps: (1) generating a low-frequency AC signal and injecting the low-frequency AC signal into the vehicle body; (2) obtaining U through a first-level measurement circuit _{9_30} ; _9‑30 The average value in one cycle reflects the unbalanced condition of the positive and negative poles to the body resistance; the variation dU in half a cycle _{9_30} Participate in the calculation of the resistance value of the second-level measurement as the fluctuation parameter of the bus voltage; (3) obtain the AC voltage amplitude U through the second-level measurement circuit _{9_25} , a single insulation resistance R = F (U _{9_25} )*W, W is the weight, W=f(dU _{9_30} ); (4) Take the average value of each measurement to obtain the vehicle body insulation resistance Ravr=(w1*R1+w2*R2+.....Wn*Rn)/(w1+w2+....Wn). On the basis of the original low-frequency signal injection method, the present invention correlates the weight of the weighted filter when calculating the insulation resistance with the variation of the DC bus voltage fluctuation, the weight is small when the bus voltage fluctuates greatly, and the weight is large when the bus voltage fluctuates small, thus Make the test results tend to be stable and reliable.

The invention relates to an edge-preserving self-adaptive weighted filtering method for natural scene images. The method comprises the following steps of firstly, calculating a Gaussian template according to the standard deviation of a Gaussian filter, obtaining depth clues in an original image by adopting a dark channel transcendental method, and carrying out normalization to form a depth transcendental image; secondly, calculating a spacial adjacent weight of each coordinate point on the Gaussian template, and calculating the luminance/color similarity weights of two pixels on the original image; calculating the depth difference weight between the two pixels on the original image, and calculating a self-adaptive weighted filtering template of the center of the template corresponding to the pixels; and finally, calculating a self-adaptive weighted filtering result of each pixel in the original image. The method takes into consideration on the characteristic that the sensitivities of eyes to luminance difference and color difference are different during the calculation of the luminance/color similarity weights, so that the method is applicable to biological models.

An object of the present invention is to improve a problem of the decrease in the internal tearing strength and water repellency in accordance with the decrease in the basis weight of a filter medium for air filters, and to provide a filter medium for air filters that can also address a demand for flame retardancy. The low-basis-weight filter medium for air filters according to the present invention is characterized by glass short fibers (A) and short fibers of hydrophobic chemical synthetic fibers each having a fiber diameter of 5 μm or less (B), as raw material fibers of the filter medium, by a mass ratio (A/B) in the range of from 70/30 to 95/5; a hydrophobic synthetic resin-based binder is added to the filter medium by 3 to 10 parts by mass of with respect to 100 parts by mass of the raw material fibers; and the filter medium has a basis weight of from 25 g/m² or more to 50 g/m² or less.

A radar system includes an image forming circuit that provides a two-dimensional image of an operating environment. The image includes pixel elements representative of the operating environment. The system includes at least one filter configured to convert the two-dimensional image into a clutter classification map of clutter regions. A predetermined number of clutter regions are selected as training cells for a predetermined cell-under-test (CUT). A space-time adaptive processor (STAP) is configured to derive a weighted filter from training cell data. The STAP applies the weighted filter to a digital return signal associated with the predetermined CUT to provide a STAP-filtered digital return signal having the clutter signal components substantially eliminated therefrom.

The invention relates to a directional weighted interpolation-based CFA (color filter array) image demosaicing method and belongs to the image processing technical field. The method include the following steps: a green plane in a CFA image is estimated, appropriate weights are assigned to each estimated value, a directional gradient is calculated, and interpolation is performed on the green plane;with an inverse gradient adopted as a weighting factor, a five-point gradient inverse weighted filtering method is adopted to optimize interpolated pixels; interpolation is performed on missing red and blue portions; the interpolated red and blue portions are optimized; and an entire panchromatic image is reconstructed, and the demosaicing of the image is completed. The directional weighted interpolation-based CFA (color filter array) image demosaicing method provided by the invention has a good effect in the reconstruction of irregular edges and the preservation of subtle details and has a superior capacity in preserving texture details. The directional weighted interpolation-based CFA (color filter array) image demosaicing method provided by the invention generates fewer visible color artifacts such as zipper artifacts and false color artifacts that vary along abrupt change colors compared with other methods.

The invention discloses a computed tomography (CT) image rebuilding accelerating method based on compute unified device architecture (CUDA). A device using the method mainly achieves data asynchronization parallel processing and comprises a data reading module, a CT data weighted filtering module based on a ground power unit (GPU), a CT image rebuilding back projection module based on the GPU and a data output module. By means of a CUDA stream technology, application programs achieve task level parallelization, namely the GPU can execute two or more different tasks parallelly.

The invention discloses a high-precision dip estimation method, which comprises the following steps of: firstly, calculating a gradient vector; then, turning over a vector field; calculating the vector set distance; calculating vector filtering weighting; and finally, carrying out vector weighting filtering processing. According to the method, the space consistency of dip estimation in a lineup single-direction extending area can be kept, and the dip estimation precision of the dip estimation method on a fault and the stratum structure with angular unconformity and fold morphology is improved. The algorithm content of the technical scheme is easy to realize and has high calculation efficiency. Meanwhile, the size of an analysis window can be flexibly regulated to satisfy the requirement of different dip estimation effects; for seismic data with severe noise interference, the space consistency of the dip estimation result can be improved by adopting a big analysis window; and for seismic data with a high signal to noise ratio, the dip estimation result precision of the fault and the angular unconformity area can be improved by adopting a small analysis window.

The present invention provides an FPGA based general multimode image preprocessing method comprising steps as follows: a processor sets image storing modes for a preprocessing circuit, which are three modes in total: an original image mode, a self-adaption grey weighted filtering mode and a window mode; in the original mode, sequentially storing data into an off-chip memory according to row and field signals; in the filtering mode, after conducting self-adaption gradient weighted filtering on image data, only storing the original grey value, filter grey value and row position information and column position information of active pixels which are larger than 0; in the windowing mode, conducting a window capturing process, in which the first byte of each frame of image data is a window number, the second byte is a row number, and the subsequent bytes are pixel data; computing the storage position of the first pixel in the row according to the window number and the row number, and then storing subsequent pixel data using the position as the head address. The present invention improves storage efficiency of an image preprocessing circuit and improves the processing and operation performance of system.

The invention discloses an image weighted filtering method relating to the processing of digital video images. The image weighted filtering method includes the following steps: setting the threshold value and the weighting coefficient of a noise point; separating a luminance component out of an image signal; judging the property of a pixel point to be processed; and processing the pixel point by an undirected filtering module and/or a directed filtering module according to the property of the pixel point. The image weighting-filtering method can maintain clear edges and details of an image simultaneously when eliminating image noise, thereby greatly improving the picture quality effect of image processing. The image weighted filtering method realizes the processing of both video images and static images, thus having a very broad applicable range.

There is provided a speech encoder comprising a first weighting means for performing an error weighting on a speech input. The first weighting means is configured to reduce an error signal resulting from a difference between a first synthesized speech signal and the speech input. In addition, the speech encoder includes a means for generating the first synthesized speech signal from a first excitation signal, and a second weighting means for performing an error weighting on the first synthesized speech signal. The second weighting means is also configured to reduce the error signal resulting from the difference between the speech input and the first synthesized speech signal. There is also included a first difference means for taking the difference between the first synthesized speech signal and the speech input, where the first difference means is configured to produce a first weighted error signal. The speech encoder also includes a means for generating a second synthesized speech signal from a second excitation signal, and a third weighting means for performing an error weighting on the second synthesized speech signal. The third weighting means is configured to reduce a second error signal resulting from the difference between the first weighted error signal and the second synthesized speech signal. Then there is included a second difference means for taking the difference between the second synthesized speech signal and the first error signal, where the second difference means is configured to produce a second weighted error signal. Finally, there is included a feedback means for using the second weighted error signal to control the selection of the first excitation signal, and the selection of the second excitation signal.

Layered code-excited linear prediction (CELP) speech encoders have progressively weaker perceptual weighting filters for each of the successive enhancement layers and decoders have progressively weaker short-term postfilters for increased bit rates (increased number of enhancement layers decoded) and a long-term postfilter for all bit rates.

The invention discloses a Beidou deformation monitoring and positioning method based on fuzzy confidence filtering. The method comprises the following steps of: firstly, dividing a monitoring period into a plurality of sub-periods, and calculating a positioning result of each sub-period; then according to satellite distribution, error sources and a satellite epoch number of each sub-period, adopting a fuzzy set theory to determine the fuzzy confidence of each positioning result; and finally, utilizing the fuzzy confidence to carry out weighted filtering so as to obtain a final positioning result of the whole monitoring period. According to the invention, the positioning calculation process is detailed, each factor influencing the positioning precision is fully considered, and the final positioning result is enabled to achieve a higher positioning precision; and especially when the weather changes in the monitoring period, the method has obvious advantages in positioning precision, so that the method has a wide application prospect.

A method of recovering texture information for an error block in a video stream includes applying an edge detection spatial filter on blocks surrounding an error block to detect texture edges, each block containing a plurality of pixels, and identifying first pixels surrounding the error block having texture data above a predetermined threshold value, selecting first pixels and checking the texture data of pixels extending from the selected first pixel in a plurality of predetermined directions for determining a direction of the texture edge, accumulating the edge detection filtering results of pixels that are located on the texture edge in a selected direction, determining the filtering weights corresponding to each direction of the texture edge based on the filtering results of pixels checked in the predetermined directions, and reconstructing the texture of the error block in the spatial domain using weight filtering based on the texture data of surrounding pixels.