248 results about "Wavelet filter" patented technology

A method and apparatus are provided for improving compression efficiency or picture quality by selecting a wavelet transform technique suitable to input video/image scene characteristics in video/image compression. The video encoder includes a temporal transform module that removes temporal redundancy of an input frame and generates a residual frame, a selection module that selects an appropriate wavelet filter among a plurality of wavelet filters having different taps according to a spatial correlation of the residual frame, a wavelet transform module that generates wavelet coefficients by performing wavelet transform on the residual frame using the selected wavelet filter, and a quantization module that quantizes the wavelet coefficients.

A face recognition method and apparatus using extended Gabor wavelet features are provided. In the face recognition method, extended Gabor wavelet features are extracted from a face image by applying an extended Gabor wavelet filter, a Gabor wavelet feature set is selected by performing a supervised learning process on the extended Gabor wavelet features, and the selected Gabor wavelet feature set is used for face recognition. Accordingly, it is possible to solve problems of a high error rate of face recognition and low face recognition efficiency caused from a limitation of parameters of the Gabor wavelet filter. In addition, it is possible to solve the problem of increased calculation complexity caused from using an extended Gabor wavelet filter and to implement robust face recognition which is excellent in dealing with a change in expression and illumination.

There are provided a watermark information embedding device and a watermark information detection device which can correctly extract classified information. In the watermark information embedding device, a plurality of dot patterns the wave directions and/or wavelengths of which are changed depending on dot arrangements are prepared, one symbol is given to one of the dot patterns, and the dot patterns are combined and arranged, so that the classified information is given. The watermark information detection device includes two-dimensional wavelet filters the number of which is equal to the number of dot patterns and which have the same wave directions and the same wavelengths as those of the dot patterns. Convolutions between an arbitrary region in a watermarked image and the plurality of two-dimensional wavelet filters are calculated, and it is determined that the dot pattern corresponding to the two-dimensional wavelet filter having the maximum convolution is embedded in the region.

The invention discloses a fault diagnosis method for a rolling bearing, and belongs to the technical field of fault diagnosis and signal processing analysis. High-frequency sampling and preprocessing of vibration signals are firstly performed on the rolling bearing with faults, the preprocessed signals are sequentially filtered by the aid of a Morlet wavelet filter, spectral kurtosis and unit spectral kurtosis of the filtered signals are calculated, and a filter parameter corresponding to the maximum value of the unit spectral kurtosis is selected by comparison, namely, a global optimization filter parameter is selected. According to the fault diagnosis and detection method, an operator can extract the optimal filter parameter in the diagnosis process without a lot of detection experience and numerous historical data, the method is wider in application range, errors caused by human errors are greatly decreased, the extracted optimal filter parameter can be more accurate, a diagnosis result is more correct, fault diagnosis and detection automation is more facilitated, more time is saved, and efficiency is higher.

The present approach relates to the use of machine learning and deep learning systems suitable for solving large-scale, space-variant tomographic reconstruction and/or correction problems. In certain embodiments, a tomographic transform of measured data obtained from a tomography scanner is used as an input to a neural network. In accordance with certain aspects of the present approach, the tomographic transform operation(s) is performed separate from or outside the neural network such that the result of the tomographic transform operation is instead provided as an input to the neural network. In addition, in certain embodiments, one or more layers of the neural network may be provided as wavelet filter banks.

The invention provides a bearing fault diagnosis method and system device based on improved empirical wavelet transform. The method comprises: step one, collecting different fault bearing signals as analysis signals and converting a time domain waveform into a frequency domain waveform; step two, drawing an upper envelope of a frequency spectrum and transforming a frequency peak with a tight support into a flat top; step three, screening flat tops in the frequency domain based on criteria, removing meaningless flat tops, and keeping a main frequency; step four, using a minimum value between adjacent flat tops as the boundary of spectrum segmentation; step five, establishing wavelet filters respectively for segmented frequency spectrums and decomposing the signals into N mode components; step six, calculating similarity values between mode components and the original signals by using a cross-correlation coefficient and selecting a component with the highest similarity value; and step seven, taking a fault sample, calculating an IMF component with the largest correlation coefficient of the sample, calculating a multi-scale entropy of the IMF component, and drawing the multi-scale entropy curve of the sample to realize fault classification.

The invention provides a corrosion detection method for a grounding net, as well as a system. The method comprises the steps as follows: the corrosion potential of detected grounding net metal is measured, constant current step signals are applied to the detected grounding net metal, and the constant current step response signals are collected; the wavelet filter treatment is performed to the collected grounding net soil corrosion electrochemical detection data; and the corrosion electrochemical parameter analysis processing is performed to the grounding net soil corrosion electrochemical detection data after the wavelet filter treatment, thereby generating the grounding net soil corrosion detection result. The grounding net corrosion status is detected accurately and conveniently by the electrochemical detection method.

The invention relates to an equipment health state evaluation and recession prediction method based on multi-channel sensing signals. The operation steps of the method are as follows: the first step: joint noise filtration of the multiple sensing signals: adopting a multi-scale wavelet filtering algorithm to perform the joint noise filtration on the multi-channel sensing signal collected from equipment so as to improve the quality of the multiple sensing signals; the second step: generation of an original characteristic set; the third step: extraction of local characteristics of the signals; the fourth step: modeling of a reference self-organizing mapping model; and the fifth step: health quantitative evaluation and residual life prediction. By adopting the method, the quantitative evaluation and the life prediction of performance recession of the equipment can be realized, the operation reliability of the equipment can be further improved and the maintenance cost can be reduced.

A compression and decompression system in which a reversible wavelet filter are used to generates coefficients from input data, such as image data. The reversible wavelet filter is an efficient transform implemented with integer arithmetic that has exact reconstruction. The present invention uses the reversible wavelet filter in a lossless system (or lossy system) in which an embedded codestream is generated from the coefficients produced by the filter. An entropy coder performs entropy coding on the embedded codestream to produce the compressed data stream.

A method and modem for communicating serial input data over a transmission link. Serial input data is partitioned into parallel data elements prior to rotation by an invertible linear mapping. Resulting frames of parallel signal elements sequentially modulate a carrier, which is then transmitted over the link. After receipt of the modulated carrier from the link, the signal is demodulated and assembled into frames of parallel signal elements which are de-rotated by an inverse linear mapping. Thresholding the result of the inverse mapping recovers the parallel data elements, which are then re-assembled into serial output data. The linear mapping employs: 1) commuting rotation matrices for convolutionally rotating data vectors into signal vectors and vice-versa; 2) filter bank polyphase rotation matrices; or 3) computationally efficient multi-rate wavelet filter banks. Transmitter pre-emphasis places most of the information in lower baseband frequencies; complimentary de-emphasis occurs in the receiver. Logarithmic amplification of the baseband signal prior to carrier modulation improves modulation gain and transmit channel noise attenuation. Coefficients of the rotation matrix of the receiver are adaptively equalized to correct for transmission path distortion. FM double-side band is employed in systems requiring minimized cost and complexity. FM single-side band is employed in systems in which bandwidth reduction is desirable. AM is also employable.

An iris identifying-method based on wavelet transform zero cross presentation includes carrying out binary state treatment on original image based on certain threshold to raise rough positioning precision of pupil, making double-threshold treatment based on external edge rough positioning of iris and carrying out intermediate value filtering to pick up general part of iris effectively, making quick and accurate rough positioning, accurately positioning external edge of iris by utilizing rough positioning result and using wavelet filter to carry out iris coding to effectively pick up information.

A 3D face recognition method based on intermediate frequency information in a geometric image as follows: (1) preprocessing a library and test models of 3D faces, including 3D face area cutting, smoothing processing and point cloud thinning, and discarding the lower portion of the face; (2) mapping the remainder of the face to a 2D grid using grid parameters, and performing linear interpolation on the 3D coordinates of the grid top to acquire the 3D coordinate attributes and generating a geometric image of a 3D face model; (3) performing multi-scale filtering with a multi-scale Haar wavelet filter to extract horizontal, vertical, and diagonal intermediate frequency information image images as invariable facial features; (4) calculating the similarity between the test model and the library set model with a wavelet domain structuring similarity algorithm; and (5) judging the test and library set model models with the maximum similarity belong to the same person.

A curved wavelet transform and a related image/video compression system are disclosed. The curved wavelet transform (CWT) is carried out by applying one-dimensional (1-D) wavelet filters along curves, rather than along only horizontal and vertical directions. The image/video compression system includes a curve determination unit, a curved wavelet transform unit, a wavelet coefficient quantization unit, a wavelet coefficient coding unit, and a curve coding unit. The quantization and coding of the wavelet coefficients are related to the curves. In one embodiment, recursive wavelet filters are used for inverse wavelet decomposition. The system provides higher compression capability than conventional wavelet-based image compression systems.

The present invention relates to a transmitter and method employing a multi-carrier transmission method, especially utilizing real coefficient wavelet filter banks. The transmitter includes a preamble data generator, a modulator, and a ramp processor. The preamble data generator generates preamble bit data, and outputs the preamble data. The modulator modulates the preamble data, generates a plurality of subcarriers, and outputs a composite wave of the time waves of the plurality of subcarriers. Subsequently, the ramp processor performs ramp processing on the composite wave with a certain delay period from a reference position of the composite wave.

Provided is an inter-frame wavelet coding apparatus that can reduce the computation complexity of a decoder by adjusting a decomposition level and a filter length based on the information amount of a frame during wavelet transform and a method therefor. The inter-frame wavelet coding apparatus includes: a Motion Compensated Temporal Filtering (MCTF) unit for computing a motion vectors of a group of pictures (GOP) and filtering the GOP with respect to the temporal axis, to thereby obtain filtered frame; a wavelet transforming unit for performing spatial wavelet transform on the filtered frame and outputting a wavelet coefficient; a quantization unit for quantizing the wavelet coefficient; an entropy coding unit for entropy-coding the motion vector computed in the MCTF unit and the quantized wavelet coefficient, to thereby generate an entropy-coded bit stream; and a wavelet filter managing unit for selecting a decomposition level and a filter length for the wavelet transforming unit based on motion estimation information of the GOP video computed in the MCTF unit, wherein the decomposition level and the filter length are included in the entropy-coded bit stream.

The invention relates to a contourlet transformation-adaptive medical image fusion method based on non-sampling and belongs to the field of image processing. The method comprises the steps that firstly, a source image is subjected to arithmetic average filtering and then is decomposed through an orthogonal 9-7 wavelet filter and a pkva filter during non-sampling to obtain low-frequency sub-band coefficients and all band-pass direction sub-band coefficients; secondly, the low-frequency sub-band coefficients are selected and fused according to the edge information maximum criterion, all the band-pass sub-band coefficients are selected and fused through an adaptive PCNN model based on a visual neuron model; lastly, a final fused image is obtained by means of inverse transformation of NSCT. According to the contourlet transformation-adaptive medical image fusion method based on non-sampling, the algorithm is very effective and correct, the edge and space texture information of the fused image is clear, color distortion is low, the false contour phenomenon does not exist, and feature information of the source image is well reserved.