40 results about "Biorthogonal wavelet" patented technology

The invention publishes a medical image ROI compression method based on a lifting wavelet and a PCNN, which comprises the following steps of: circling a region of interest by a doctor, and separating the region of interest from a region of no interest by a difference image method; adopting lossless compression in the region of interest, constructing compactly supported biorthogonal wavelet transformation through a lifting scheme, and then carrying out Huffman encoding; adopting lossy compression in the region of no interest, segmenting gray-value pixel approximate points through the PCNN, carrying out ignition operation, and then carrying out run-length encoding; and finally carrying out inverse transformation restoration, merging the region of interest and the region of no interest, and eliminating a boundary discontinuity problem through linear interpolation. Experimental results prove that the region of interest can be flexibly selected and controlled by the compression method, the used information for doctor diagnosis can be completely reserved, and the compression ratio is higher. Meanwhile, the computation for an ROI mask and the computation and the encoding for a wavelet coefficient difference value are omitted, the compression and decompression time and the algorithm complexity are reduced, and the image processing and transmitting efficiency is improved.

The invention discloses a current alarm signal processing method for an improved mathematical morphology filter. Pulse and noise interferences are removed by a mathematical morphology method and various frequency spectrum interferences of harmonic waves and the like are removed by a wavelet method, so that a better effect of inhibiting the interferences is obtained and a more pure fundamental wave current is obtained for processing a power alarm signal. The current alarm signal processing method comprises the following steps of: a first step of obtaining current waveform data by utilizing a current transformer and a data acquisition hardware circuit; a second step of carrying out alternate hybrid filtering processing on the current signal by the mathematical morphology method through adopting a cosine structural element so as to filter out the pulse and noise interferences; and a third step of carrying out multi-scale wavelet decomposition on the current signal by adopting a biorthogonal wavelet with a linear phase, selectively reserving low-frequency and high-amplitude wavelet coefficients by setting a threshold value and finally, carrying out signal reconstruction by utilizing the reserved wavelet coefficients so as to remove various frequency spectrum interferences of the harmonic waves and the like and obtain a fundamental wave power signal.

The invention relates to a target selecting method based on transient visual evoked electroencephalogram, comprising the following steps: VC + + writing visual stimulator evokes an electroencephalogram signal, 16-lead collecting device collects an electroencephalogram signal VEP which is amplified by an electroencephalogram amplifier and A / D converted, so that the signal is input into a computer and memorized in a memorizer in a way of signal voltage magnitude; B sample band biorthogonal wavelet method is used for extracting an electroencephalogram characteristic signal, in addition, corresponding results are classified, identified and output by the self-learning ability of BP neuronic network; wherein, the method also comprising the following steps of: designing the accurate timing visual stimulator by CPU timestamp; answering the output impulse of paralled port; collecting the electroencephalogram signal VEP by a collecting device; pretreating the collected signal; extracting the electroencephalogram signal by the B sample band biorthogonal wavelet method; and classifying characteristic quantity by the BP neuronic network. The method has the advantage that the BP neuronic network is used for effectively improving signal to the noise ratio and the recognition rate of visual evoked potential VEP.

The invention discloses a second generation small-wave support vector machine assessment method for damage and remaining life of a metal structure. According to the method, an intrinsic mode function is obtained through decomposition of an experience mode, a time-frequency domain statistic characteristic of the intrinsic mode function is extracted, a most sensitive characteristic is chosen according to a distance accessment principle to construct a best characteristic set, a minimum quantization error indicator which has an obvious performance degradation trend along with time changes is constructed by means of self-organization neural network characteristic fusion techniques, a biorthogonal small-wave support vector machine kernel function of second generation small-wave transform is provided, a service life prediction model of the second generation small-wave support vector machine is constructed, the minimum quantization error indicator serves as a prediction characteristic, and quantitative assessment for the damage and the remainig service life of a metal structural component of mechanical equipment under a small subsample is achieved.

The invention relates to a method for enhancing images based on multi-scale edge detection in anti-symmetric biorthogonal wavelet reconstruction, aiming at realizing enhancement of image edges in thereconstruction process of wavelet tower-type data resolution. The method comprises the following steps: carrying out multi-scale wavelet decomposition on images; calculating a module value graph and aphase angle graph according to a semi-construction result, carrying out module maximum value detection and threshold value processing and extracting edge images of the scale in the wavelet reconstruction of each level; enhancing corresponding edge points of the semi-reconstruction image according to the edge images; continuing reconstruction to obtain the enhanced low frequency component of the last scale; and carrying out wavelet reconstruction level by level in terms of the reconstruction enhancement process of each level starting from the level of the most coarse resolution to realize image enhancement. The method for enhancing images can be widely used in fields about improving digital images such as medical imaging, biological features recognition, vehicles driving assistance, military, man-machine interaction and the like.

This invention introduces a class of multi-band linear phase lapped biorthogonal transforms with fast, VLSI-friendly implementations via lifting steps called the LiftLT. The transform is based on a lattice structure which robustly enforces both linear phase and perfect reconstruction properties. The lattice coefficients are parameterized as a series of lifting steps, providing fast, efficient in-place computation of the transform coefficients as well as the ability to map integers to integers. Our main motivation of the new transform is its application in image and video coding. Comparing to the popular 8.times.8 DCT, the 8.times.16 LiftLT only requires 1 more multiplication, 22 more additions, and 6 more shifting operations. However, image coding examples show that the LiftLT is far superior to the DCT in both objective and subjective coding performance. Thanks to properly designed overlapping basis functions, the LiftLT can completely eliminate annoying blocking artifacts. In fact, the novel LiftLT's coding performance consistently surpasses that of the much more complex 9 / 7-tap biorthogonal wavelet with floating-point coefficients. More importantly, our transform's block-based nature facilitates one-pass sequential block coding, region-of-interest coding / decoding as well as parallel processing.

This invention introduces a class of multi-band linear phase lapped biorthogonal transforms with fast, VLSI-friendly implementations via lifting steps called the LiftLT. The transform is based on a lattice structure which robustly enforces both linear phase and perfect reconstruction properties. The lattice coefficients are parameterized as a series of lifting steps, providing fast, efficient in-place computation of the transform coefficients as well as the ability to map integers to integers. Our main motivation of the new transform is its application in image and video coding. Comparing to the popular 8×8 DCT, the 8×16 LiftLT only requires 1 more multiplication, 22 more additions, and 6 more shifting operations. However, image coding examples show that the LiftLT is far superior to the DCT in both objective and subjective coding performance. Thanks to properly designed overlapping basis functions, the LiftLT can completely eliminate annoying blocking artifacts. In fact, the novel LiftLT's coding performance consistently surpasses that of the much more complex 9 / 7-tap biorthogonal wavelet with floating-point coefficients. More importantly, our transform's block-based nature facilitates one-pass sequential block coding, region-of-interest coding / decoding as well as parallel processing.

The invention discloses a data acquisition method for multi-parameter real-time monitoring. In the data acquisition method, the latest compressive sensing technology is employed. a plurality of sensing parameters acquired for each sensor node is firstly observed and coded by using a random matrix and then sent to a remote real-time data monitoring terminal by wireless transmission. When the monitoring terminal receives data, a data reconstruction model is established by reconstructing a biorthogonal wavelet transformational matrix capable of performing sparse representation on the sensing data; and finally high-precision reconstruction of the multi-sensor data is completed by using an orthogonal matching pursuit (OMP) algorithm. The data acquisition method can realize high-precision construction by using a small amount of observation data, is suitable for situations that node resources in a wireless sensor network are limit and data transmission volume is large, effectively prolongs a life cycle of a sensor network, increases wireless transmission efficiency and robustness of the multi-parameter monitoring, and further enhances the real-time performance of the system monitoring.

The invention provides a method for generating an up sampling filter and a down sampling filter, which comprises: processing down sampling and up sampling on the video signals fitting a markov mode to attain reconstruction signals; calculating out the energy of the reconstruction signals; according to the biorthogonal wavelet theory carrying parameters and the energy of the reconstruction signals, calculating out the parameters of the wavelet filter corresponding to the maximum energy of the reconstruction signals, to generate an up sampling filter and a down sampling filter. The invention further provides a method for adopting an up sampling filter and a down sampling filter to realize spatial graded video code, a device and a system. The invention can minimize the coding energy loss, to improve the quality and performance of video signal coding.

The invention discloses an underwater image enhancement processing method which combines a homomorphic filtering method with a biorthogonal wavelet threshold filtering method. The underwater image enhancement processing method mainly includes the following steps: A), performing logarithm operation on an original image acquired underwater to acquire Z (x,y); B), performing discrete Fourier transformation on Z (x,y) to acquire Z (u,v); C), performing homomorphic filtering processing on Z (u,v) to acquire S (u,v); D), performing Fourier inversion on S (u,v) to acquire s (x,y); E),performing exponent operation on s (x,y) to acquire a processed image g (x,y); F), applying the biorthogonal wavelet threshold filtering method to process the image. By the underwater image enhancement processing method, noise of the image can be removed, contrast ratio of the image is increased, illumination uniformity of a processed underwater image is improved, both balanced filtering and median filtering of a peak signal to noise ratio (PSNR) histogram are improved, underwater image quality is improved, and the underwater image enhancement processing method has certain practical value in improving underwater image quality.

The invention discloses a method for constructing a biorthogonal wavelet filter bank. The method includes the following steps: determining the length N of a decomposition low-pass filter h(n) and the length M of a reconstruction low-pass filter (please see the specifications) according to the requirements of wavelet functions to be constructed, wherein the N and the M are even numbers; determining the orders of vanishing moments of dual wavelet generating functions (please see the specifications) to be constructed; calculating the biorthogonal complete reconstruction filter bank according to a formula set to obtain a set of coefficients of the biorthogonal complete reconstruction filter bank; substituting the results into a dual-scale equation to construct a set of biorthogonal wavelet bases (please see the specifications), decomposing a decomposition high-pass filter corresponding to the wavelet function (please see the specifications), and reconstructing a reconstruction high-pass filter corresponding to the wavelet function (please see the specifications). Compared with common db-series wavelet filter banks and common bior-series wavelet filter banks, heart sound signals are processed through the biorthogonal wavelet filter bank constructed with the method, and the better noise reduction effect, the accurate heart sound classified information and the smaller reconstruction error rate can be obtained.

The present invention discloses a method for realizing three-dimensional reconstruction by multi-spectral image fusion, comprising the following steps of: realizing biorthogonal wavelet decomposition; determining fusion operators; implementing HIS transform, and separation of space and spectral characteristics; combining bands; fusing a resulted image. After processing with the method for realizing three-dimensional reconstruction by multi-spectral image fusion, an internal structure of a three-dimensional structure is quite clear, and therefore digital effect of the multi-spectral image is optimal, and complementation of advantages of single spectrum information is realized.

The invention relates to a mine image intensification method. Multi-dimensional, dissymmetric and biorthogonal wavelet decomposition and reconstitution are performed on mine original images through an A'trous algorithm and image intensification aiming at a wavelet coefficient is performed through a single threshold function, a dual threshold function and a soft threshold function. According to the mine image intensification method, the intensification processing is performed twice through an edge detection capability of the dissymmetric and biorthogonal wavelet transform and simple threshold functions to achieve the mine image edge intensification, so that the mine images are clear, mine production, detection and other requirements are satisfied and the problem that obtained mine image edges are blurred due to limitation of underground coal mine conditions is solved.

The present invention belongs to the field of biological characteristic distinction, and is especially the method of extracting geometric characteristic of iris based on characteristic edge distribution. The method includes first defining geometric characteristic of iris and describing its reliability and stability; subsequent extracting geometric characteristic edge of iris in antisymmetric double orthogonal wavelet process and constituting overall edge distribution characteristic in unequal interval grading according to the inhomogeneous distribution of geometric characteristic of iris; and finally introducing characteristic distance expression and proposing legal user judging method. The method has high distinction precision and less outer factor influence.

The invention discloses a wavelet base construction method for a ground penetrating radar signal based on a lifting scheme. A method for constructing a matched wavelet according to a biorthogonal wavelet theory and target signal waveform characteristics is provided for a problem of extraction of the characteristics of a hole detection signal at the back of a tunnel lining. The method is based on aperfect reconstruction filter condition and a lifting scheme wavelet, different lifting operators and dual lifting operators are acquired by carrying out lifting and dual lifting on an initial biorthogonal filter, and the actual characteristics of the ground penetrating radar signal is combined to construct a new biorthogonal wavelet base which not only meets the linear phase and the tight support but also has the advantages of being high in signal matching degree with the ground penetrating radar signal and the like. According to the wavelet base construction method for the ground penetrating radar signal based on the lifting scheme, the wavelet base is applied to quantitative analysis of hole defects of an indoor hole detection test, and compared with other types of wavelets, the wavelet constructed by the lifting scheme can more accurately identify the time and the position of a mutation point of the hole defect signal, and quantitative analysis of the position and the vertical dimension of the hole defect in the tunnel engineering can be realized more accurately, so that the reliability and accuracy of the ground penetrating radar on the defect detection are greatly improved.

The invention provides a farming data collecting and transmitting method, and relates to the technical field of agricultural farming data transmitting and processing. A sensor node collects original monitoring data, the original monitoring data are subjected to compressed sensing through a compressed sensing theory to obtain a sensing parameter vector, and the sensing parameter vector is transmitted to a convergence node; the convergence node conducts dimensionality reduction processing on the sensing parameter vector, an encoding vector is obtained, and the encoding vector is sent to a back-end server through a wireless transmission channel; the back-end server constructs a biorthogonal wavelet transformation matrix capable of conducting sparse representation on the original monitoring data; and the back-end server constructs a data reconstruction model according to the biorthogonal wavelet transformation matrix, and the encoding vector is reconstructed based on an orthogonal matchingpursuit algorithm to obtain the original monitoring data. A wireless collecting and transmitting method of farming data is put forward by combining a compressed sensing technology, and thus the problems of large data size and large wireless transmission energy consumption in a network can be solved well.

The invention discloses a CDB97 wavelet transformation real-time image fusion method based on field programmable gate array (FPGA) hardware. By a CDB97 biorthogonal wavelet lifting scheme, images output by different detectors are dissected and reconstructed, and the implementation complexity of the hardware is simplified. When the hardware processes floating-point number operation, the real-time fusion of heterologous images is realized by an addition and multiplication operation method under a simplified A (1,6,5) floating-point number standard on the premise of meeting the wavelet forward and inverse transformation precision. By the method, the hardware processing speed of an FPGA is full exerted on the basis of meeting the fusion precision and the real-time fusion of the heterologous images is realized by using the CDB97 biorthogonal wavelet lifting scheme and combining the simplified A (1,6,5) floating-point number standard.

The invention discloses an equal-even length anti-symmetrical biorthogonal wavelet filter group based edge detection method. The equal-even length anti-symmetrical biorthogonal wavelet filter group based edge detection method comprises the following steps of performing three-layer wavelet decomposition on an image through an equal-even length anti-symmetrical biorthogonal wavelet by a Mallat algorithm; calculating a gradient vector modulus value graph and a phase angle graph according to every scale of wavelet decomposition data of the image; detecting a modulus maxima point of every scale according to the direction determined by the phase angle graph; removing pseudo boundary points by a threshold value method; integrating obtained scales of boundary point sets so as to obtain the accurate single pixel width of boundary. According to the equal-even length anti-symmetrical biorthogonal wavelet filter group based edge detection method, the wavelet decomposition is performed through an equal-even length anti-symmetrical biorthogonal wavelet filter group with the differential operator function, the boundary information of every scale is comprehensively utilized, and accordingly the integrity and the accuracy of edge detection of the image are improved and certain anti-noise performance is achieved.

The invention discloses a construction method of biorthogonal wavelet, which is based on Bernstein base and comprises the following steps that: (1) a lowpass filter at a discomposing and reconstructing end is expressed by Bernstein base; (2) numerical calculation of the lowpass filter is carried out; (3) the lowpass filter at the discomposing and reconstructing end is led to meet the conditions to reconstruct the lowpass filter entirely; (4) the parameter of obtained biorthogonal wavelet is calculated. In addition, the invention also provides a method to realize image compression based on the biorthogonal wavelet. Construction of the filter containing parameter that is provided with symmetric odd number length is realized by adopting the invention, thus providing a new way to construct transformation suitable for high-magnification compression of static image.

The invention discloses a geographic information image compression method. The geographic information image compression method comprises a step of preprocessing an image, a step of transforming the image and a step of coding the image, wherein the step of preprocessing the image comprises the steps of acquiring a geographic information image, conducting partitioning on the geographic information image according to topographical rules which comprise topographical rugged degrees, the step of transforming the image comprises the steps of conducting transformation processing on the image for each partitioning by the utilization of two-dimensional wavelet transformation, the two-dimensional wavelet transformation uses biorthogonal wavelets and is broken into two times of one-dimensional wavelet transformation to conduct processing, the two times of one-dimensional wavelet transformation are low-frequency data transformation and high-frequency data transformation respectively, processing is carried out on the low-frequency data transformation and the high-frequency data transformation in a parallel mode, and the step of coding the image comprises the steps of carrying out quantization on the image processed by the two-dimensional wavelet transformation and conducting coding for a second time, and an ECBOT algorithm is adopted by the coding. The geographic information image compression method reduces calculated amount of image processing and is high in calculating speed, and the quality of the image is not obviously affected.

The invention discloses a compression method of a geographic information image. The method includes: an image preprocessing step, obtaining the geographic information image, and partitioning the geographic information image according to a terrain rule of the geographic information image, wherein the terrain rule comprises the terrain roughness degree; an image transformation step, for each block, performing transformation processing on the image by employing two-dimensional wavelet transformation, wherein two-dimensional wavelet transformation employs biorthogonal wavelet, the two-dimensional wavelet transformation is decomposed into twice of one-dimensional wavelet transformation for processing, the twice of one-dimensional wavelet transformation includes low-frequency data transformation and high-frequency data transformation which are processed in parallel; and an image coding step, quantifying the image through two-dimensional wavelet transformation, and then performing coding, wherein the coding is performed by employing the 801 algorithm. According to the method, the calculation amount of image processing is small, the operation speed is higher, and the image quality is not substantially affected.

The invention discloses an image compression method based on biorthogonal invariant set multi-wavelets, the steps of which are: 1. input image data; 2. DC level shift; 3. composition of filter matrix judgment; Variable set multi-wavelet transform layer initialization; 5. Extend the height and width of the image; 6. Biorthogonal invariant set multi-wavelet row transform; 7. Biorthogonal invariant set multi-wavelet column transform; 8. Quantization coefficients; 9 . Arithmetic coding; 10. Rate-distortion optimized interception; 11. Code stream organization. The present invention adopts a group of biorthogonal invariant set multi-wavelet filters with symmetry, compact support and orthogonality, and adopts the method of inner product in calculation of biorthogonal invariant set multi-wavelet transform, so that the complexity of the algorithm is greatly reduced , the high concentration of energy and entropy after transformation has greater sparsity, which is beneficial to subsequent compression coding, and it is convenient for block processing and parallel acceleration.

The invention provides an SAR interferogram wavelet noise reduction processing method comprising the following steps: determining signal points and noise points in an SAR interferogram, constructing a noise point identification matrix, and only carrying out filtering noise reduction processing on the noise points; the method comprises the following steps of: extracting interference pattern data containing noise, decomposing the interference pattern data into a real part and an imaginary part, respectively performing wavelet decomposition on the real part and the imaginary part by utilizing a Biorthogonal wavelet basis, and enabling the number of layers of wavelet decomposition to be optimal by adopting a whitening test mode; carrying out noise reduction processing on a wavelet coefficient by utilizing an improved wavelet threshold function and a hierarchical threshold value obtained by a Birge-Massart penalty function in a self-adaptive manner; and wavelet reconstruction is carried out on the real part and the imaginary part after filtering and noise reduction, an interferogram after filtering and noise reduction is obtained, and a final noise reduction interferogram is obtained by combining signal points in the SAR interferogram. The invention further provides an SAR interferogram wavelet noise reduction processing device. Noise can be effectively reduced, and edge detail information can be kept.

The invention discloses a geographic information image compression method comprising the following steps: an image preprocessing step used for obtaining a geographic information image and segmenting the geographic information image according to landform rules in the geographic information image, wherein the landform rules comprise landform roughness grade; an image transformation step using two dimension wavelet transformation to transform each segment, wherein the two dimension wavelet transformation uses biorthogonal wavelets and is decomposed into two times of one-dimensional wavelet transformations for processing, the two times of one-dimensional wavelet transformations comprise low frequency data transformation and high frequency data transformation, and parallel processing of the high and low frequency data transformations can be realized; an image encoding step used for quantifying the image converted by the two dimension wavelet transformation, and encoding the converted image, wherein the encoding step uses an ECBOT algorithm. The geographic information image compression method can reduce the image processing computational complexity, is high in operation speed, and the image quality is not substantially affected.

The invention provides an audio and video system based on a geographical information system. The method includes the steps of image preprocessing, wherein a geographical information image is obtained and is partitioned into blocks according to the terrain rule in the geographical information image, and the terrain rule includes the terrain roughness degree; image transforming, wherein for each block, two-dimensional wavelet transform is used for transform processing, adopts biorthogonal wavelet and is decomposed into two-time one-dimensional wavelet transform to be processed, the two-time one-dimensional wavelet transform includes low-frequency data transform and high-frequency data transform, and the low-frequency data transform and high-frequency data transform are carried out in parallel; image coding, the image obtained after two-dimensional wavelet transform is quantified and encoded, and an ECBOT algorithm is adopted in coding. Calculation quantity of image processing is small, and operation speed is higher while image quality is not affected remarkably.

The invention discloses a current alarm signal processing method for an improved mathematical morphology filter. Pulse and noise interferences are removed by a mathematical morphology method and various frequency spectrum interferences of harmonic waves and the like are removed by a wavelet method, so that a better effect of inhibiting the interferences is obtained and a more pure fundamental wave current is obtained for processing a power alarm signal. The current alarm signal processing method comprises the following steps of: a first step of obtaining current waveform data by utilizing a current transformer and a data acquisition hardware circuit; a second step of carrying out alternate hybrid filtering processing on the current signal by the mathematical morphology method through adopting a cosine structural element so as to filter out the pulse and noise interferences; and a third step of carrying out multi-scale wavelet decomposition on the current signal by adopting a biorthogonal wavelet with a linear phase, selectively reserving low-frequency and high-amplitude wavelet coefficients by setting a threshold value and finally, carrying out signal reconstruction by utilizing the reserved wavelet coefficients so as to remove various frequency spectrum interferences of the harmonic waves and the like and obtain a fundamental wave power signal.

The invention provides a hyperspectral remote sensing image abundance estimation method and device based on conditional number weighting. The method comprises the following steps: acquiring a hyperspectral data matrix and an end metadata matrix; performing wavelet packet decomposition on the hyperspectral data matrix and the end metadata matrix by using biorthogonal wavelets to obtain corresponding wavelet packet trees; obtaining a coefficient matrix at each node of a wavelet packet tree corresponding to the end metadata matrix; calculating the condition number of each coefficient matrix; calculating the weight of each node according to each condition number; and taking the hyperspectral data matrix and the end metadata matrix corresponding to each node as the input of the least square method, multiplying the result output by the least square method each time by the weight of the corresponding node, and finally summing each node to obtain an abundance estimation result. According to the method, the conditional number of the coefficient matrix after wavelet packet decomposition is used for weighting, effective information in the data can be utilized to a greater extent, and therefore the least square estimation is improved, and the unmixing precision of the hyperspectral remote sensing image is improved.

The invention provides a multi-band wavelet transformation method for image and video compression coding and decoding. The method comprises: performing forward or reverse conversion of image compression or decompression by adopting r-band discrete biorthonormal wavelets with decimal notation r more than or equal to 16. The multi-band wavelet transformation method can be applied to computer software, digital signal processor (DSP) software, application specific integrated circuit (ASIC) chips or field programmable gate array (FPGA) chips. The invention provides the novel multi-band wavelet transformation method, which has the advantage that a wavelet conversion image does not have blocking effect, avoids complex iterative algorithm of wavelet transformation, and the multi-band wavelet can be transformed into product of wavelet transformation and blocking transformation to organically associate the wavelet transformation and blocking transformation, so that seamless downward compatibility of the novel and existing technologies can be realized, namely the existing technology is a standard subset of the novel technology, and the novel technology can successfully decode images or videos coded by the existing technology and contributes to realization of parallel calculation.

The invention discloses a glaucoma detection method based on Radon domain feature representation, which comprises the following steps: step 1: converting the color fundus image into a grayscale image, and performing grayscale image preprocessing; step 2: under n projection angles Radon transform is used to project the preprocessed grayscale image into the Radon domain to obtain a one-dimensional discrete signal; Step 3: Unify the dimensions of the one-dimensional discrete signal, and use biorthogonal wavelet to decompose the one-dimensional discrete signal to extract the approximate coefficient and Detail coefficient; Step 4: Combine the approximation coefficient and detail coefficient of each group of one-dimensional discrete signals into a sample feature input classification detection model to obtain glaucoma detection results; the input parameters for classification detection model training are glaucoma fundus image samples and normal fundus images The samples constitute the eigenvector matrix N and the sample label vector for each row in the eigenvector matrix N. The present invention can accurately detect whether it is glaucoma through the above method.

The present invention provides a multi-bank wavelet transform method for image and video compression coding and decoding. The r-bank discrete biothonormal wavelet with the bank number r greater than or equal to 16 is applied to perform forward or inverse transform on image compression or decompression. Above-mentioned multi-bank wavelet transform method can be applied to computer software, DSP software, ASIC chip or FPGA chip. The present invention provides a new multi-bank wavelet transform method. It has the advantages that images haven't blocking effect after wavelet transform, and avoids complicated iterative calculation in wavelet transform. And such multi-bank wavelet transform can be translated into the product of wavelet transform and block transform. Wavelet transform and block transform are integrated dynamically,thus enabling seamless downward compatibility of new and old technology, that is, the old technology is a standard subset of the new one. The images or videos coded with the old technology can be decoded smoothly using the new technology, which is favorable to parallel calculation.