37 results about "Hypercomplex number" patented technology

The invention relates to a fast and parameter sectional type self-alignment method for a strapdown inertial navigation system. A coarse alignment process is finished through an analysis method, and then horizontal precise alignment and directional precise alignment are conducted. The directional precise alignment is divided into three stages, and each stage selects different adjustment time and attenuation coefficient to determine alignment parameters according to characteristics of the stage. Acceleration correction and angular velocity correction are calculated based on the alignment parameters, input acceleration information and angular velocity information are corrected, an initial attitude angle is obtained through hypercomplex number calculating by using corrected information, and a precise alignment process is finished. The fast and parameter sectional type self-alignment method finishes initial alignment through an analysis method and a compass method by collecting data of a gyroscope and an accelerometer, other sensor information is not required, and safety and security of the initial alignment are guaranteed. The fast and parameter sectional type self-alignment method selects the optimum adjusting time and attenuation coefficient according to alignment characteristics of different stages to calculate other alignment parameters, fast convergence performance and anti-interference performance of an alignment curve are improved.

The invention discloses a measuring method for a carrier gesture of an optical fiber gyro, which comprises determining an initial position parameter and an initial speed value of a carrier through an external device, initially aligning strapdown inertial navigation system of the optical fiber gyro, determining an initial gesture of the carrier which is relative to a navigation coordinate system, obtaining an initial value of a gesture hypercomplex number, determining a gesture renewal cycle H = tm-tm-1, calculating a increment delta phi of rotating vector through collecting a carrier which is output by the optical fiber gyro which is corresponded to an angle speed of the inertial coordinate system, obtaining a gesture renewal hypercomplex number q(H) of the gesture renewal cycle H through a relation of the rotating vector and the hypercomplex number, renewing the gesture hypercomplex number through a renewal equation of the gesture hypercomplex number, calculating a strapdown matrix T that a carrier coordinate system b is relative to a navigation coordinate system n, and obtaining a gesture angle of the carrier which is relative to the navigation coordinate system and the like. The invention solves the problem that a cone effect influences a measuring accuracy of the carrier gesture under a high dynamic environment of a carrier or a high-frequency vibration environment.

The present invention belongs to image signal processing field, in particular a significative digital watermarking algorithm of the supercomplex frequency domain. The algorithm processing quick supercomplex Fourier transform to the color carrier image, selecting proper frequency band to embed in the watermark data in the supercomplex frequency domain, and repairing the value of coefficient of asymmetry, resolving the problem of the precondition of the supercomplex frequency domain embedding in the watermark, ensuring process transmittion by the red, green, blue of the color image when embedding in the watermark image, paving a road for further study of the color image watermarking algorithm of the supercomplex frequency domain. The algorithm also provides a regulation of ''intersecting redundancy embed'' of the watermark data, further improving the Robust of the digital watermark. The analyzing result shows that the proposed method diffuses the error caused by watermark to the whole imge by supercomplex Fourier transform, and diffuses to each weight of red, green, blue colors, achieving excellent combination of the non intangibity and safety of the digital watermark.

The invention provides a color image authentication method and system based on hypercomplex number encrypted domain sparse representation. The color image authentication method comprises the steps of generating a phase mask according to a Logistic chaotic sequence, carrying out double random phase encryption on a color image by adopting quaternion Fourier transform so as to acquire ciphertext data, carrying out sparse representation on a component of the ciphertext data by using a sparse matrix so as to acquire a sparse ciphertext, wherein the component comprises a real component and an imaginary component, decrypting the sparse ciphertext, calculating a nonlinear correlation coefficient of a decrypted image, and carrying out authentication on the color image according to a centralized peak value. The color image authentication method based on the hypercomplex number encrypted domain sparse representation in the embodiment of the invention has high security, and a certain degree of noises can be resisted, thereby being suitable for being applied to the fields of secret communication and authentication of images.

The invention discloses a detection method based on fusion of a visible light image and a corresponding night vision infrared image, and belongs to the field of machine vision. The method comprises the specific steps as follow: for a visible light image, getting a saliency image of the visible light image using a deep learning network and an incremental coding length method; for a night vision infrared image, getting a saliency image of the night vision infrared image using a GBVS model and a spectrum scale space method based on a hyper-complex frequency domain; and fusing the two saliency images to get a final saliency image. The time domain and the frequency domain are fused. In view of the fact that energy radiation difference is also a factor influencing saliency, the night vision infrared image is processed. The saliency region of the visible light image is extracted using the incremental coding length method. The method is not limited to extraction of low-level features, but also can be used to extract high-level semantic features through a deep learning network. Therefore, the extraction of the saliency region is more comprehensive and more accurate.

The invention belongs to colorful target tracking technical field, specifically a target tracking arithmetic of combination of 'supercomplex cross correlation' and 'target-center distance weighing'. Most target tracking arithmetic extract gray level information of a colorful target as tracking features, which losses color information of the target. Almost all colorful target tracking methods are the simple expansions of gray level image processing method and cannot represent color relation of the colorful target. Even if color difference between two colorful objects is high, gray levels thereof may be similar to each other, so that mis-matching may be caused by conventional real number matching method. The invention employs supercomplex cross correlation method to process the colorful image as a vector, which provides the whole colorful feature of the target and provides more useful information for matching the target. By combining supercomplex cross correlation and 'target-center distance weighing' to improve anti-jamming ability for target tracking, accurate tracking on a colorful target is realized more successfully.

The present invention belongs to the image signal processing field, in particular a self-adapting watermark algorithm of a color image supercomplex frequency domain. Fistly, the algorithm processes a quick supercomplex Fourier transform to color carrier image, selecting proper frequency band in the supercomplex frequency spectrum real component, masking the vein, edge and brightness of the color carrier image by the human visual system, bestowing different masking intensities to the selecting frequency bands to embed watermark, achieving a self-adapting watermark algorithm of a color image supercomplex space. The result shows that the self-adapting masking of the color image greatly improve non intangibity and safety of the supercomplex frequency domain watermark algorithm, and having better aggressivity than the supercomplex frequency domain watermark algorithm having non-self-adapting mask; contrast to the present documents, the advantages of the invention are verified.

The invention belongs to the field of image fusion technology, in particular to a multi-spectral image and panchromatic image fusion method based on residual hypercomplex symplectic decomposition. The method comprises the following steps of : respectively constructing models of residual images of a multi-spectral image and a panchromatic image by using hypercomplex, and respectively subjecting the hypercomplex residual models of the multi-spectral image to hypercomplex symplectic decomposition along the grayscale axis direction to obtain a simplex portion containing brightness information and a perplex portion including chromaticity information. The analysis shows that the residual of the multi-spectral image with high resolution can be recovered by substituting the simplex portion obtained by decomposing the low-resolution multi-spectral image with hypercomplex residual image of a high-resolution panchromatic image, and the fusion of the multi-spectral image and the panchromatic image can be achieved by synthesizing symplectic decomposition. The simulation result shows that the invention is free of visible spectral distortion. The evaluation result of various prior image fusion methods shows that the invention is superior to HIS, PCA and wavelet transformation fusion method.

The invention relates to a color image digital watermark method capable of resisting stamping, printing and scanning processes and belongs to the technical fields of anti-counterfeit, authentication and information safety. The invention adopts the technical scheme that an L*a*b* color space of a color carrier image is represented by quaternary supercomplex number; readable watermark information is encoded and modulated to generate a two-dimensional watermark signal in a form of the quaternary supercomplex number; and the watermark embedding position is determined by a uniform discrete logarithmic polar coordinates method. The color image digital watermark method capable of resisting stamping, printing and scanning processes has the beneficial effects that the embedding capacity of watermarks is large; the robustness resisting synchronous distortion is strong; the gap of an image quality evaluation function of the color image is filled; self-adaption embedding of the watermarks with highest strength is realized; the robustness resisting rotation, compression, stamping, printing and scanning attacks is strong; and the method can be widely applied to anti-counterfeiting domain authentication of various certificates and printed products.

The invention is a color image quality evaluation method based on super-complex relating to image quality evaluation technical field. It describes three-color R, G, S values of color image as a whole super-complex vector, and indicates the common quality indexes of color image which are based on five combinations of color image false, correlating expense, luminance distortion, contrast and color distortion. According to HSI (hue, saturation, brightness) color model, the relationship between the mentioned common quality indexes of color image and gray image is discussed. The experimental results from various color image distortions show that the mentioned common quality indexes are not only prior to the existing method on the assessment of gray part, but also able to determine the distortion mainly occurs in the structure or color information.

The invention belongs to the image signal processing technique field. Particularly the invention relates to a a color fault image evaluating method based on a supercomplex heterochromia conversion. Currently quality evaluation for the color fault image or extracting luminance information of color image, or separately processing each component of the color image and then averaging, such all neglect color association of the image and usually cannot gain the exact color fault image evaluation. The invention partitionings the whole image, processes a specifically supercomplex rotating for fault image piece so as to gain the fault image and heterochromia among the original images, and averages the heterochromia of all pieces to process the color fault evaluation of the whole image. A experiment proves that, for the color fault image, the invention can gain an evaluate result corresponding to subjective visual effects, and the invention also has the advantages of simple operating, small calculated amount, superior to the method of extracting the luminance information of the color image to process to evaluate, and also having a better effect than the method of separately processing each component of the color image and then averaging.

The invention discloses a significant target detection method based on a hypercomplex Fourier transform and a mean shift, comprising the following steps: S1, inputting a hypercomplex matrix, defininga hypercomplex matrix; S2, inputting an image and defining a hypercomplex representation of the image; S3, a spectrum scale space being proposed to process the amplitude spectrum of different scales,and a single parameter smooth spectrum series is generated, which is parameterized by the scale of Gaussian kernel; S4, according to a group of spectral scale spaces obtained by the multi-scale frequency domain waves, and the original phase spectrum and the Euler spectrum, salience maps of different scales being calculated; S5, image segmentation being performed by mean shift; S6, a threshold selection method being proposed, in which a threshold value (Ta) is determined to be twice the average significance of a given image; S7, color reproduction of the salient target. The invention can eliminate the repetitive complex background, effectively suppress the complex background, and accurately locate the prominent target.

The present invention belongs to the technical field of image signal processing, in particular to a hyper-complex Fourier transformation and a rapid algorithm correlated with the hyper-complex of a colorful image. The colorful image is disposed as a vector entity by the hyper-complex, compared with the traditional algorithm, the color association of the image can be described better, and the hyper-complex cross correlation is widely applied on multiple field of the colorful image disposition. At present, the ''decomposing and transforming method'' and the ''decomposing vertical and parallel vector method'' are mainly applied in the colorful image disposition to make the rapid calculation of the hyper-complex Fourier transformation and the hyper-complex cross correlation. The present invention expands the signal disposition of the hyper-complex according to the real part and each imaginary part, and separately calculates by utilizing the traditional rapid Fourier transformation FFT tool, and restores the relative unit vector, and provides a new rapid algorithm for the hyper-complex Fourier transformation and the hyper-complex cross correlation of the colorful image. The analysis shows that compared with the existing rapid method, the algorithm is simple and convenient, and the amount of calculation is smaller.

The invention discloses a USDC data processing method which comprises the following steps of color image wavelet decomposition, wherein hypercomplex wavelet transform is adopted, and color information of color images is maintained; vector encoding, wherein a hypercomplex cluster analysis process is adopted, and human eye sensitive information content in the images is maintained; motion compensation, wherein asymmetric crossed multilevel hexagonal-grid improved search is adopted, classification is carried out according to motion intensity, and compressed bit flow is obtained; finally the compressed bit flow is output through a network. The technological mode of combination of the color image wavelet decomposition, the vector encoding and the motion compensation is adopted, so that video transmission code flow becomes small, video images are compressed according to the image conditions, bandwidth is greatly saved, delay is reduced, and operating cost is saved.

The invention discloses a speckle noise suppression method based on a hypercomplex wavelet amplitude soft threshold and relates to an image denoising method in the field of image processing. In order to overcome the defect that the conventional wavelet threshold cannot reach an optimal effect, the speckle noise suppression method comprises the following steps of: 1, performing HWT (hypercomplex wavelet transform) on a noise image to obtain a hypercomplex wavelet coefficient; 2, converting the hypercomplex wavelet coefficient represented by a real part and an imaginary part into an amplitude-phase representation form; 3, estimating the noise threshold of the hypercomplex wavelet amplitude coefficient; 4, performing soft threshold processing on the hypercomplex wavelet amplitude coefficient according to the noise threshold; and 5, combining the processed hypercomplex wavelet amplitude coefficient and an unprocessed phase system, and performing hypercomplex wavelet inverse transformation to obtain the image denoising result. According to the method, the capacity of representing the hypercomplex wavelet phase texture can be exerted, so that the approximate optimal threshold of the noise suppression is selected; and moreover, the texture structure information of the image is kept, and an ideal image denoising result is obtained.

The present invention discloses a hypercomplex number-based polarimetric SAR image multi-channel joint matching method. The method comprises the steps of firstly carrying out the Pauli decomposition on the polarimetric SAR images, constructing a Pauli vector hypercomplex number form of the polarimetric SAR images, and then carrying out the symplectic decomposition on the Pauli vector hypercomplex numbers, carrying out the fast Fourier transform based on a decomposition result, and finally obtaining a matching position of the to-be-matched polarimetric SAR images by calculating the hypercomplex number phase correlation. The experimental results show that the method disclosed by the present invention still can obtain the accurate matching result and has a better matching performance even on the conditions that the local difference exists between the polarimetric SAR images, and the multiplicative noise is contained.

The disclosure relates to a method of processing a complex signal comprising acquisition of a signal in the form of complex numbers; determination on the basis of the complex signal acquired of the associated hypercomplex components, said components corresponding to at least derivatives with respect to time of the phase of the complex signal acquired; processing of the hypercomplex signal thus determined in such a way that the signal resulting from the processing comprises a greater number of components than the number of components of the signal acquired.

Improvements to optimal interval operators are developed for interval expression evaluation using arithmetic and real power operators applied to complex and hypercomplex number systems. A method for determining efficacy of numeric precision, incorporating minor changes to interval operators, provides detection of insufficient numeric evaluation precision.

The invention discloses an urban noise identification method based on a hypercomplex random neural network. According to the method, urban noise signals pass through a spectral subtraction filter, then MFCC, LSP and PLP features of the urban noise signals are extracted and spliced into a quaternion augmentation vector, and finally classification and recognition of the noise signals are achieved through a quaternion extreme learning machine (Q-ELM). According to the method, useful information in the signal is fully extracted under the condition of a low signal-to-noise ratio, the augmented quaternion structure can also utilize structural information among features, and the recognition rate of the urban noise signal can be effectively improved.