457 results about "Filter window" patented technology

Techniques for removing ringing artifacts from video data. A deringing filter in accordance with the present invention preserves real image edges in a video frame, while smoothing out the interiors of objects. In one aspect, a 9-tap low-pass filter is applied to an adaptive processing window. The filter window is initialized with the values in a 3×3 mask centered on the position whose output is computed. Then all values that are very different from the central one are replaced with the central value. The deringing filter varies between 3×3 low-pass and identity, depending on how much the central value differs from its surrounding ones. A deblocking filter in accordance may also be suitably used in conjunction with the deringing filter.

The invention relates to a filter window for EUV lithography comprising a pellicle, a wire structure for supporting the pellicle, characterized in that the pellicle comprises a first layer comprising at least one of AlN, Ru, Ir, Au, SiN, Rh, C. A pellicle with these materials has a very low EUV absorption in combination with a minimal oxidation rate. In a particular embodiment, the thickness of the pellicle is between 30 nm and 100 nm. It can be easily checked that absorption of EUV radiation of such a thin pellicle is equal to known filter windows, i.e. about 50% at a wavelength of 13.5 nm wavelength, but the oxidation of the pellicle according to the invention is much smaller. The filter window can for example be used to separate a Projection Optics box and a wafer compartment of the apparatus or to shield a reticle from particle contamination.

An invention provides a system and method for filtering pixels in an image using only fixed-point and summation operations. First, a filtering window is centered on an input pixel. Based on a difference between the intensity of the input pixel and its neighboring pixels, fuzzy filter weights are obtained. A sum of the fuzzy filter weights is used to determine a normalization factor. Then, the pixel intensities, fuzzy filter weights and the normalization factor are used to obtain an output pixel corresponding to the input pixel.

The invention discloses a preparation method of a zirconia grinding fluid, and relates to the technical field of new materials applied in precision grinding and polishing technical fields. The preparation method comprises the processes: adding a wetting and dispersing agent to high-speed dispersed water in parts by weight, then adding zirconia powder and auxiliary materials, fully dispersing, introducing into a high-speed sanding machine for sanding to grind the edge of zirconia powder into a round spherical shape, adding functional additives when the particle size of the zirconia powder reaches a certain value, and then adding a coloring agent to adjust the color. The zirconia grinding fluid has the characteristics of free from influence of particle size and shape of zirconia raw materials, lower production cost and good stability, is suitable for the precision grinding and polishing of liquid crystal electroconductive glass, flat optical glass, optical spherical and optical lens glass, filters, filter windows and glass plate substrates, and is especially suitable for the grinding and polishing of soft material spherical glass.

The invention discloses a method and device for obtaining a wheel set tread contour line of an urban rail train. The device comprises two sets of 2D laser displacement sensors installed on the two sides of a rail in a mirror symmetry mode. The laser detection faces of the two sets of sensors are located on the same plane, and the integral device is lower than the rail surface. The method comprises the steps that after the sensors detect wheels at the same time to obtain detection point coordinates, the output points of the two sets of sensors are combined to a same coordinate system through coordinate transformation and coordinate translation; the x-coordinate value of the right end face of a tread is obtained, and a filtering window is established based on the x-coordinate value to remove interference points of measuring data; the x-coordinate value of the right end face of the tread is obtained, and measured data points are divided into K number sets according to the actual situations; least squares curve fitting is carried out on the data points of each number set; coordinate values of segment points are obtained, and each segment curve is smoothened into an integral tread contour line according to the lagrange multiplier method. The method and device have the advantages of being high in speed and precision, easy to operate, capable of carrying out online non-contact type measurement, and the like.

In a face recognition apparatus adapted to recognize an input face image on the basis of one or more registered face images, similarity between an input face image and a registered face image is determined based on a Gabor jet calculated by performing Gabor filtering using Gabor filters defined by a Gaussian function representing a window and sine and cosine functions representing a frequency response for each of predetermined frequency values and for each of predetermined angles of the response function. Values of the filter window are calculated in advance based on the Gaussian function and stored in a filter window data ROM. Values of the response function are calculated in advance for respective angles based on the sine and cosine functions and stored in sine data ROMs and cosine data ROMs. In the Gabor filtering process, coefficients of the Gabor filters are determined from values read from these ROMs.

The invention discloses a repeated alarm processing method based on data filtering, and belongs to the technical field of alarm management. The method comprises the following steps of: optimally designing variable alarm processing parameters by virtue of variable historical process data, and storing the obtained optimal alarm processing parameters in an alarm parameter database; acquiring real-time process data from a real-time database or a distributed control system (DCS); then obtaining window filtering parameters from the alarm parameter database, and filtering the real-time process data;and finally carrying out repeated alarm judgment on the filtered real-time process data, automatically inhibiting the repeated alarm if the repeated alarm is judged, and otherwise displaying alarm information. The repeated alarm processing method has the beneficial effects that the noise effect in the real-time process data is eliminated, the quantity of occurrence of repeated alarms is reduced and the purpose of alarm management in the process industry is achieved.

The invention discloses a method for suppressing random noise in seismic exploration based on VMD-TFPF, which includes the following steps: (1) decomposing a noisy signal; (2) calculating the cross correlation coefficient, and judging modal components needing to be filtered; (3) filtering modes screened out; and (4) getting a de-noised signal through calculation. Seismic random noise can be effectively attenuated, and the effective signal amplitude can be well maintained in the filtering process. The algorithm of the scheme is easy to implement, and is of high operability. The problem of time-frequency peak filtering window size selection is avoided. The method is suitable for de-noising complex signals.

The present invention relates to a lithium tantalate film infrared detector and the preparing method thereof. The invention comprises the following components: an infrared filtering window, a resonance chopped wave modulator, a focusing lens, a pyroelectric lithium tantalate film infrared measuring probe, a heat sink cavity, a preamplifier, a low-pass filter, an electric power and signal output interface, a casing and an environment temperature detecting filter. The method for preparing the detector comprises the following steps: selecting a substrate, growing a SiO2 layer on the front and back surface, depositing Si3N4 layer on the front surface in sequence, sputtering a Ti layer, sputtering a photoetching Pt electrode layer, producing a lithium tantalate film layer, depositing a phototeching Al electrode layer, growing a photoetching SiNX antireflection layer and sputtering a black layer to complete the double unit structure infrared probe. The focusing lens is coated with an anti-reflection film. The infrared window is pasted with a narrowband filtering film. The preamplifier is built with a JFET tube or operational amplifier. The low-pass filter is built with an operational amplifier. The resonance chopped wave modulator is driven by piezoelectricity or electromagnet, and the resonance frequency is 1Hz-1000Hz.

The invention discloses a Chinese hedge scope detection method based on a stacked neural network. The Chinese hedge scope detection method is characterized by comprising the following steps: carrying out word segmentation processing on sentences which contain hedges in a to-be-analyzed experimental corpus; carrying out syntactic parsing on the sentences after the word segmentation processing by employing a syntactic parser to obtain a phrase structure tree of the sentences; finding candidate phrases via a phrase-based candidate sample screening strategy, thereby determining boundary words of the candidate phrases, including left boundary words and right boundary words; respectively filtering the left and right boundary words as well as context information of the hedges by employing filtering windows; taking the left and right boundary words as well as the context information of the hedges as candidate sample word sequences and mapping to a real number vector space to convert into a word vector form; inputting a stacked learning model LSTM (Long Short Term Memory networks)-CNN (Convolutional Neural Network) based on a combination of the LSTM and the CNN for learning to obtain boundary classifiers; and carrying out classification on test data to obtain classification results of left and right boundaries.

Radiosondes (200) and related radiosonde systems (500) include a plurality of different sensors (105, 218, 237, 239) for acquiring sensor data related to atmospheric data, wherein the plurality of sensors consist of a single humidity sensor (105) that is within a sealed housing (120). The sealed housing (120) includes a hydrophobic filter window (130) that allows in ambient gases while preventing entry of condensed forms of moisture from entering the sealed housing (120). A wireless transmitter (255) including an antenna (228) is coupled to an output of the plurality of sensors (100, 218, 237, 239) for transmission of the sensor data over a wireless path to at least one ground based receiver. The radiosonde (200) is generally exclusive of any heater.

The invention discloses a non-local mean value image denoising method based on a filter window and parameter adaption. According to the invention, firstly, noise is detected, and a noise calibration matrix is established according to a detection result; the size of the noise calibration matrix is consistent with the size of an image, and the matrix value at a corresponding position of each noise point is set to be 1, and the matrix value at a corresponding position of each non-noise point is set to be 0. Then, each pixel of a noise image is successively taken as a reference point, and centric to the point, a predetermined number of non-noise reference points are taken in a counterclockwise direction to be involved in computation. Finally adaptive weighting parameters are determined according to the locations of the reference points, and a weighted result is calculated and a restored pixel value is obtained; the corresponding element in the noise calibration matrix is set to be 0 and the pixel point after denoising can be used as a reference point of other noise points. Compared with traditional image denoising methods, the method provided by the invention is added with the noise detection and noise point screening, thus improving algorithm accuracy, changing a reference point selection window and improving algorithm adaptability.

The invention discloses an image impulse noise removing method for preventing edge blurring. Edge pixel determination, impulse noise determination and filter processing are carried out respectively; an edge pixel is processed independently; and noise points in other pixels are processed by means of consistent weight mean filtering by selecting filter windows with different sizes. According to the method, edge pixel determination is carried out; an edge pixel is determined according to the characteristic of a large difference of pixel values around the edge pixel point of the image; noise removing is carried out by using an independent way, so that image edge information can be kept well to prevent an edge blurring phenomenon. During an impulse noise filtering process, no fuzzy rule needs to be designed; and because no threshold selection needs to be carried out, the calculation efficiency is improved. The method is suitable for noise removing of images with different pollution degrees.

The invention relates to an image processing method for filtering mixed noise and belongs to the image processing technical field. The image processing method for filtering the mixed noise comprises enabling a filter window center and pixel points of coordinates in the image to achieve superposition by building the filter window; obtaining mid-values of gray values of all the image pixel points in the filter window and determining a range of the gray values by utilizing threshold values; obtaining mean values as pixel point gray values of the image coordinates according to the sum of the pixel gray values and the pixel point numbers within the obtained range of the gray values; obtaining all the pixel point gray values of all the coordinates of the entire image to achieve the entire image processing in the same manner. The image processing method for filtering the mixed noise has the advantages of being capable of effectively filtering the impulse noise by choosing the mid-values as the center of the gray level window; restraining the gaussian noise by setting the threshold values to determine the range of the gray values according to the actual conditions and performing average on the pixel point gray values which fall within the range; not only effectively filtering the mixed salt and pepper noise and the gaussian noise, but also being simple in algorithm and being small in calculated amount simultaneously and being beneficial to the real-time application of the engineering.

The invention discloses a plant three-dimensional reconstruction method and system based on depth map repair. The method comprises the following steps: obtaining a plurality of views; obtaining a depth map corresponding to each view, and recording the depth map as a first depth map; repairing a cavity area in the first depth map, and dynamically adjusting the size of a filtering window in a repairing algorithm by using super-pixel block label information; performing filtering processing on the repaired first depth map to obtain a second depth map; carrying out fusion processing on the second depth map to obtain a plant dense point cloud model; and extracting a plant three-dimensional surface from the dense point cloud model by using a surface reconstruction algorithm to complete the reconstruction of the plant three-dimensional model. The method is simple to operate and low in cost. The size of the filtering window is dynamically adjusted by using the boundary information of the super-pixel block, so that pixels which do not belong to the same depth area do not participate in filtering calculation, the occurrence of errors is reduced, plant dense point clouds are more dense, and afinally reconstructed plant model is more accurate and complete.

The invention discloses a low-altitude target tracking system based on a FPGA. The low-altitude target tracking system comprises an image acquisition module for initially configuring a video decoding chip, wherein the image acquisition module decodes a data format on a video decoding chip bus to extract a video field, line and effective pixel data, and extracts the pixel gray level; the to-be-processed pixel and neighborhood value are registered in the preprocessing module to form a filter window, the FOFI and the data in the register are updated once at each gray level clock so as to obtain a new filter window; the data in the filter window is sorted and selected to obtain a filter mid value; a target segmentation module for performing sub-window region average gray value computation, dynamic dual-threshold computation and binarization; a target positioning module for performing centroid computation and prediction; a communication module for sending a target centroid coordinate; and a cradle head control module for controlling a cradle head to rotate according to the centroid position of a target, and controlling the target at the view center of a camera.

The invention discloses a method and device for quickly processing a signal base line. By utilizing the important information that the sample data is increased point by point, a quick median calculation method is provided and a median filter is realized on such basis, wherein the operation of removing the signal base line is realized by subtracting a median filter output result from an original data. The method comprises the following steps: a) selecting a proper filtering window length k, using a current processing point as a reference point, and filling the filtering window with proper data sequence; b) if the current point is a starting point, searching for the data in the filtering window and outputting the median as the signal base line of the current processing point; c) if the current point is not the starting point, calculating the median in the filtering window by using the quick median calculation method and outputting the median as the signal base line of the current processing point; and d) subtracting a signal base line output value of the current processing point from a collected current processing point value and outputting the result as a data removing the signal base line.

The invention discloses a stratum structure self-adaption median filtering method. The method comprises the steps of: 1, calculating a gradient structure tensor; 2, calculating a stratum lateral incontinuity measurement; 3, structuring a structure self-adaption median filtering device; and 4, performing structure self-adaption median filtering and processing. By utilizing the method, earthquake random noise and part coherent noise can be effectively attenuated, and stratum edge and detailed structure characteristics such as effective signals, geologic faults and amplitude abnormalities can be maintained in a filtering process; the algorithm of the technical scheme is easy to realize and has good operability; and moreover, a selection problem of a median filtering processing window size is avoided, the method meets the requirements of the median filtering processing of complicated signals, for data areas with good event extension, the filtering performance of the median filtering device is improved through adaptively controlling the direction characteristics of a filtering window, and for areas with geologic faults and angular unconformity, the maintaining performance of the median filtering device to stratum edge structures such as the geologic faults is improved through adaptively adjusting the size of the filtering window.

A water curtain filtering window device for filtering particle matter (PM) 2.5 by using air energy is provided with a water curtain filtering device and an air energy water heater. An exhaust fan of the air energy water heater is used for exhausting indoor contaminated air outdoors, meanwhile an evaporator is used for absorbing indoor air heat energy, and cold water is heated to be hot water by using a condensing pipe. The water curtain filtering device uses the hot water to generate a filtering water curtain, prevents the filtering water curtain from being frozen by cold air, outdoor fresh cold air is sucked indoors through a ventilator, the filtering water curtain is used for absorbing dust and the PM 2.5 in air, and fresh purified air is provided for the indoor space.

The invention discloses a depth image enhancement method based on anisotropic diffusion. The similarity among pixel points of a color image corresponding to a depth image is used as a basis of depth diffusion, and based on the known depth of the depth image, filling of a depth missing region of the depth image is finished. Through the depth image enhancement method based on the anisotropic diffusion, the defect that in a traditional depth enhancement method based on interpolation, edges of an object are blurry is overcome, meanwhile, the limit of the size of a wave filtering window in a depth enhancement method based on wave filtering is broken through, and the depth image enhancement method based on the anisotropic diffusion has the advantages of being high in universality, high in robustness and the like. The depth image enhancement method based on the anisotropic diffusion can be widely used for a variety of depth images which have missing depth regions, and in a practical application process, based on the color image and the depth image which are in correspondence to each other, a good depth image missing region filling effect can be achieved.

A method and apparatus are disclosed for identifying and removing banding artifacts (i.e., false contours) resulting from insufficient bit depth caused by digital image quantization, conversion, and/or compression. This method includes: explicitly identifying texture block and flat block; de-termination of filter window sizes with the consideration of handling transitions between texture block and flat block; de-banding filtering with edge protection; and noise shaping according to de-banding filter result.

The invention, which belongs to the technical field of computer vision images, discloses a local-information-based infrared weak target detection method in a complex background. According to the invention, a filtering structure is constructed by using one point v0 in a to-be-detected image as the center, wherein the filtering structure includes a protection frame and a filtering window; a plurality of directions that use the point v0 as the center and point to the filtering window are found out, wherein the plurality of directions are evenly distributed; weighted gray values from the protection frame to the filtering window in the multiple directions are calculated respectively and one value closest to the point v0 gray value among obtained results is used as a background estimation valueof the point v0; the filtering window slides in the to-be-detected image to obtain background estimation value of all points and a background estimation image is formed; the background estimation image and the to-be-detected infrared image are differentiated to obtain a difference image; and then target segmentation and extraction are carried out on the difference image to obtain a target detection result. With the method provided by the invention, clutter interferences of the edge information and the edge intersection part in the complex background can be suppressed effectively; adaptation tothe bright and dark targets is improved; and the target detection effect is improved effectively.

A parallel scanning system of an infrared touch screen which uses polaroid sheets comprises an infrared element, infrared filter windows, corresponding drive circuits and corresponding signal processing circuits as well as a microcontroller system. The invention is characterized in that the infrared element is divided into a plurality of modules that are numbered; the infrared filter windows in front of each module are internally provided with the polaroid sheets with the same polaroid direction; the polaroid directions of the polaroid sheets in front of two neighboring modules on the same frame are reverse; the drive circuits in each module are the same; the input ends thereof after being connected in parallel are connected with the output ends of the address drive data of the microprocessor system; the module also comprises an infrared signal processing circuit; the detection signal output end of the infrared signal processing circuit is connected with the microprocessor system through a group symbol coder or directly connected with the microprocessor system. The invention divides the touch screen into a plurality of detection areas of small areas and carries out detection, thereby extensively improving the response speed of the touch screen. Besides, as the structures of the modules are the same, the design, manufacture and maintenance costs of the touch screen are reduced.

The invention relates to a baseline drift removal method and device and a median filter. The baseline drift removal method comprises the following steps: acquiring sampling point signal values with preset number to form an initial sort column; sorting the initial sort column from small to large to obtain an initial median; acquiring the next sampling point signal value, putting at the end of the initial sort column, and deleting a first sampling point signal value in the initial sort column to form a current sort column; acquiring the median of the current sort column according to the next sampling point signal value and the initial median; and calculating the signal value of removed baseline drift according to the median of the current sort column and the next sampling point signal value. In the baseline drift removal method and device and the median filter, all signal sampling points in each filter window do not need to be sorted, thereby, the baseline drift removal process is simply, conveniently and rapidly accelerated; and when the median is acquired, the next sampling point signal value and the median in the last sort column are selectively judged in sequence of magnitude, and further, the speed of a fast algorithm is increased.