50results about How to "High structural similarity" patented technology

The invention discloses a face super-resolution processing method based on K neighbor sparse coding average value constraint, relating to the technical field of image resolution processing, in particular to a face super-resolution processing method based on K neighbor sparse coding average value constraint. The method comprises the following steps of: according to prior information of the position of a face block, clustering image blocks of a training sample to obtain a pair of high-and-low-resolution sparse representation dictionaries in relevant positions; performing sparse representation on K neighbor of the input image block with the low-resolution dictionary, thus obtaining sparse coding average values; and realizing the sparse representation of a low-resolution image block based on sparse prior and K neighbor sparse coding average value constraint, realizing the reconstruction of a high-resolution image block through coefficient mapping, and finally overlapping and averaging to obtain a high-resolution face image. According to the method, on the basis of keeping the similarity of the reconstructed face image, the definition of the face image is improved, and the quality of the super-resolution image is enhanced.

The invention discloses a cross-modal medical image registration method. The method comprises the following steps: providing a training set comprising a floating image of a first modal and a referenceimage of a second modal; inputting the floating image into an image conversion network, and converting the floating image into a conversion image of a second modal; inputting the floating image and the reference image into a cross-modal flow sub-network to output a first deformation field; inputting the converted image and the reference image into the single-mode flow sub-network to output a second deformation field; inputting the first deformation field and the second deformation field into a deformation field fusion network to output a final deformation field; inputting the floating image and the final deformation field into a space transformation network to obtain a floating image after distortion transformation of the final deformation field; obtaining a first total loss function according to the transformed floating image and the reference image, and performing supervised training on the network by taking minimization of the first total loss function as a target; and inputting ato-be-registered image into the trained network to obtain a registered image. The cross-modal medical image registration method can greatly improve the cross-modal medical image registration effect.

The invention provides a telescopic video sparse information processing system, belonging to the technical field of information processing. The system comprises a time domain resolving module, a double multi-resolution ratio geometry resolving module, an entropy coding module, a bit stream multiplexer module and a rate distortion optimization controlling module, wherein the time domain resolving module is connected with the double multi-resolution ratio geometry resolving module to transmit time domain high-frequency video frame information and time domain low-frequency video frame information; the double multi-resolution ratio geometry resolving module is connected with the entropy coding module to transmit double multi-resolution ratio geometry-transformed resolution ratio information; the entropy coding module is connected with the bit stream multiplexer module to transmit configured multi-layer bit stream information; the rate distortion optimization controlling module is connected with the time domain resolving module to transmit motion evaluating control information; and the rate distortion optimization controlling module is connected with the entropy coding module to transmit coding control information. The system has the advantages of high compatibility, large compression ratio, high coding efficiency and small code word overhead, can obtain better visual effect, and has wide applicability.

The invention discloses a scannable image generation method fusing digital coding and belongs to the field of QR code generation technology. According to the method, first, a to-be-fused image is processed based on a locally adaptive image brightness adjustment algorithm, and image colors are highlighted; second, a saliency region of the image is extracted, a weight matrix for adjusting the priority of a QR code module is obtained, and the QR code module is adjusted through Gaussian elimination; and last, the to-be-fused image with adjusted brightness and a QR code obtained after module adjustment are fused based on the weight matrix, and a final scannable QR code image is generated. The generated QR code is compatible with a coding / decoding standard of a traditional QR code, and on the premise of guaranteeing scanning robustness, the visual effect of the QR code is greatly improved, the conflict between the aesthetic sense and the robustness of the QR code is well solved, and the application scene of the QR code is expanded.

The invention discloses an image super-resolution method based on dictionary learning and non-local total variation. The image super-resolution method based on the dictionary learning and the non-local total variation mainly solves the problems of ring effect, lost high-frequency information, and inaccuracy of boundary matching of a super-resolution method and the like. The achieving steps include (1), inputting an image training set; (2) using a KSVD algorithm to train two corresponding high-resolution dictionary and a low-resolution dictionary; (3) conducting sparse representation of a low-resolution input image, and determining sparse coefficient; (4) using determined sparse coefficient and the high-resolution input image to obtain a high-resolution image; (5) conducting ring effect removal of the non-local total variation on the reconstructed high-resolution image; (6) conducting high-frequency information enhancing of the high-resolution image by error compensation, and obtaining a final result. By showing of a simulation experiment, compared with the prior art, the image super-resolution method based on the dictionary learning and the non-local total variation has the advantages of being simple in operation, small in noise, clear in edge and the like, and can be used for obtaining a high-definition image.

The embodiment of the present invention provides an image data processing method. The method comprises the steps of subjecting a noise image matrix to total variation so as to obtain a first de-noised image matrix; according to the first de-noised image matrix and the noise image matrix, acquiring a residual image matrix; subjecting the residual image matrix to adaptive wiener filtering so as to obtain a filtered residual image matrix; subjecting the first de-noised image matrix, the filtered residual image matrix and a weight vector to secondary de-noising treatment according to a first preset rule so as to obtain a second de-noised image matrix. The above method fully utilizes the prior information of an image. In this way, the noise is removed, while the edge and the details of the image are better retained at the same time. A high signal-to-noise ratio is obtained, while the structural similarity is also kept at a high level at the same time. Therefore, the visual effect of people can be fully met.

The invention provides a construction method and application of a coronavirus antigen on the basis of a mosaic strategy. The method comprises the following steps of: (1) analyzing the natural structural protein of a human coronavirus, and obtaining cytotoxic T lymphocyte epitope which is in the presence on the natural structural protein; and (2) adopting the mosaic strategy to analyze the structural protein of the human coronavirus, and after rare epitope with low occurrence frequency in the natural structural protein is removed, obtaining the coronavirus antigen assembled by short peptides. According to the construction method, on the basis of an artificial intelligence algorithm, all known CoV (coronavirus) genomic sequences are subjected to big data analysis, and a novel antigen sequence is designed on the basis of the mosaic strategy. A novel antigen covers most CTL (cytotoxic T lymphocyte) epitope of natural S, M, N and E proteins on all seven known HCoVs (human coronavirus), hasa structural similarity with a natural protein, and has a potential application prospect and value on an aspect of preparing a coronavirus universal vaccine.

The present invention provides a method of lowering intraocular pressure which comprises administering a therapeutically effective amount of a pharmaceutical composition comprising 4-bromo-5-(2-imidazolin-2-ylamino)benzimidazole, or a salt thereof to the affected eye of a patient, as a single dose, wherein the affected eye has an intraocular pressure less than the baseline intraocular pressure for at least eight (8) hours.

The invention includes methods of representing polymer sequences in a way that reveals important position-specific contextual information. The representations can be used to determine a number of properties of polymers, such as protein and nucleic acid sequences, including the identification of secondary domain structures, folding rate constants, and the effects of altering (e.g., mutating) monomers. In addition, the representations can be used to compare polymers and thereby identify important structural and functional characteristics of polymers.

The invention discloses environment-friendly repeated-writing paper and a preparation method therefor. According to the environment-friendly repeated-writing paper and the preparation method therefor, a hydroxyl protective group is added into a nano bacterial cellulose suspension with excellent characteristics such as high water absorptivity and water retention ability and good water and air permeability, so as to lower hydrophilicity; a staged reaction is carried out under strong base conditions, so that bacterial cellulose reaches moderate water absorptivity and water retention ability, ink can only be present in a surface layer and be clear in writing while the ink is absorbed, and thus, writing, reading and subsequent handwriting wiping are facilitated; then, a scientifically-compounded dispersant is added, and ultrasonic and high-voltage pulse electric field combined dispersion is carried out, so that a stable and uniform modified bacterial cellulose suspension is obtained; finally, the surface of raw paper is coated with the suspension so as to obtain the writing paper with appropriate ink absorbing uniformity and adhesive power and a dense structure, thus, the writing property of the writing paper can be enhanced, and the clearness of writing is enhanced; and waterproofing and oil-proofing actions can be achieved, most importantly, ink marks on the paper can be erased with a cleanser and the paper can be reused for 40 to 100 times under the condition that the performance of the paper is not affected.

The invention discloses an OCTA imaging method and device based on two-dimensional composite registration. The invention discloses a two-dimensional composite registration method, a plurality of preliminary blood flow contrast images are used; after an OCTA effective strip is extracted, a global registration method based on large vessel skeleton registration degree and SIFT feature point extraction and a local registration method based on SIFT flow target function detection are used in a combined mode to perform registration on the OCTA effective strip pair on the two-dimensional level, and then motion artifacts are eliminated. The obtained fused OCTA result image is small in pixel average error, good in quality and high in structural similarity with an original OCTA blood flow contrast image, motion artifacts contained in the fused OCTA result image are greatly reduced and even disappear, and high-quality OCTA blood flow contrast imaging is achieved.

The invention discloses a simulation test device for rotor blade loss of an aero-engine and relates to the technical field of the blade loss tests of aero-engines. According to the simulation test device for the rotor blade loss of the aero-engine, the situation that a rotor blade flies out after being broken can be effectively simulated, the flying-off rotating speed of the blade can be effectively controlled, and therefore a rotor blade loss simulation test can be conveniently conducted. The device comprises a mounting rack 102 used for mounting an aero-engine rotor tester 1, a rotation driving assembly used for driving the aero-engine rotor tester 1, an L-shaped blade 201 used for simulating the blade, and an impact system 4 used for impacting the L-shaped blade 201. The device has theadvantages of wide blade loss rotating speed control range, high precision, high structural similarity, high operability, good repeatability, high safety and the like on the whole.

The invention discloses a lead-zinc flotation foam image space-time joint denoising method based on bubble motion stability analysis. The method is based on the motion characteristics of bubbles. thestable motion state (SMS) and the unstable motion state (UMS) of the foam image sub-block are accurately identified; carrying out time domain filtering denoising on the sub-blocks with the SMS characteristics based on motion compensation; and denoising the sub-blocks with UMS characteristics by adopting a spatial domain filtering method based on local spatial domain correlation, and obtaining a spatial-temporal combined denoising result of the lead-zinc flotation foam image to be processed according to the correlation coefficient of the bubble sub-blocks, the combined time domain filtering result and the spatial domain filtering result. Experimental verification is carried out in visual monitoring of the lead-zinc flotation process, the result shows that the foam image with the high signal-to-noise ratio can be obtained through the method, the structural similarity of the denoising result is high, and a foundation is laid for accurate extraction of the visual characteristics of the lead-zinc flotation foam and effective monitoring of the flotation process.

The invention discloses a cuboid surface distortion correction method, which includes: firstly utilizing an image acquisition system to acquire a rectangular image, finding four edges of a cuboid surface through edge detection, intercepting an area defined by the four edges, and then interpolating the intercepted area defined by a trapezoid to obtain a correction image. By means of determination of a vanishing line of the image, the cuboid surface distortion correction method interpolates the image proportionally in the vanishing line direction and the perpendicular direction of the vanishing line to complete correction of projection transformation and affine transformation of the image finally. The method only needs one image and can complete restoration of the original rectangular image. Length-to-width ratio of the corrected image is the same as that of an actual rectangular face.

The invention discloses an image denoising method based on level set curvature and wavelet transform, includes: performing wavelet transform stratification processing for high-density flexible substrate image containing noise, S2 extracting high-frequency component images and low-frequency component images respectively from the sliced images, S3 establishing an image level set curvature variational smoothing model for image smoothing, S4 fusing the high-frequency image after smoothing with the low-frequency image after slicing, and reconstructing to obtain the denoised image. Compared with other denoising models, the novel method of the invention has higher peak signal-to-noise ratio and higher structural similarity.

The invention belongs to the field of computer graphics and computer vision, particularly relates to an image character removing method, system and device based on a gate circulation unit, and aims tosolve the problem that characters in an image cannot be effectively removed due to the fact that accurate character strokes cannot be extracted in the prior art. The method comprises the following steps: constructing a stroke-level binary mask generation model based on one or more inverse residual modules connected in series and a gate cycle unit, and obtaining a stroke-level binary mask of an input image based on the input image and a character region mask; and constructing a character removal model based on the one or more encoders, the one or more decoders and the feature processing module, and obtaining a character-removed image based on the fusion features of the input image, the character region mask and the stroke-level binary mask. The fine stroke-level character mask can be obtained, so that the model is effectively guided to remove the characters with high quality, and the rendering and backfilling effects in the character removing process are improved.

The invention particularly relates to a silkworm silk gland recombinant expression vector for expressing a human epidermal growth factor as well as a preparation method and application thereof, and belongs to the field of biological materials. The constructed recombinant expression vector is formed by fusing a truncated fibroin heavy chain N-terminal structural domain, a C-terminal structural domain, an optimized human epidermal growth factor and a silkworm nuclear polyhedron virus enhancer, a redundant part of an endogenous fibroin extra structural domain contained in fusion protein is removed to the maximum extent, on the premise of not influencing the genetic hybridization process that the fusion exogenous target protein is integrated into a silk-based material, redundant post-translation modification existing in the fusion protein is eliminated as much as possible, so that the functional silk material for expressing the human epidermal growth factor with high biological activity is created by genetic hybridization; and a feasible solution is provided for developing a novel silk-based material with high biological activity by utilizing an advanced biosynthesis platform represented by silkworms.

In order to solve the technical problems that a traditional lens-free camera image reconstruction method is relatively sensitive to noise and relatively low in system depth of field, the invention provides a lens-free camera image reconstruction method based on a coding mask and a Learned-TSVD algorithm. The method comprises the following steps: encoding a propagation process of light by using an encoding mask, converting an original large-scale system measurement matrix into a left system measurement matrix and a right system measurement matrix which are small in scale by utilizing the separable characteristic of the coding mask and a TSVD algorithm; thirdly, constructing neural network training to circularly train the left and right system measurement matrixes, and reducing an error of an approximate operation on a final result; and finally reconstructing an image through the TSVD algorithm and a regularization algorithm. According to the method, the learned system measurement matrixes are used for subsequent calculation, so that the noise influence resistance of the whole reconstruction process is higher; scene images at other distances can be well reconstructed by using the learned system measurement matrixes, and the problem of low depth of field of other reconstruction algorithms is solved.

The invention provides a method for optimizing projection modes in image reconstruction based on compression sensing. In the process of reconstructing compressed sensing images, the traditional projection mode usually projects line signals of the image by lines, which resulting in that the row information of the image is wasted, and the sparseness of the image cannot be fully utilized; or, the whole image is pulled into one line signal to be projected, but the projection efficiency is decreased, the complexity in calculation is increased, and the image reconstruction time is prolonged. The method has the advantages that the projection mode is optimized on the basis of traditional single-side line projection, a row and line double-side projection mode with super-low sampling rate is proposed; the sparseness of the global image is fully utilized, the projection efficiency is improved, and the reconstruction accuracy and quality of the image at low sampling rate are improved; especially,under the condition of super-low sampling rate of 1 / 16, compared with the single-side projection mode, the PSNR (peak signal-to-noise ratio) of the reconstructed image of the double-side projection mode is increased by about 4.5dB, and the SSIM (structure similarity) is increased by about 0.1.

A method of selectively separating a biological target from a sample including the biological target material or suspected of including the biological target includes the steps of (i) providing a solid including ureide moieties at its surface, (ii) contacting the sample with the solid, whereby a substantial fraction of the biological target in the sample binds to the ureide moieties, and (iii) separating the solid from the sample.

The invention discloses an improved B-spline non-rigid registration method for distortion correction of an atmospheric turbulence image, relates to the field of atmospheric optics, and mainly solves the problem that the correction performance is unstable when the atmospheric turbulence image is seriously distorted in a traditional registration method. The method comprises the following steps: inputting an image sequence degraded by atmospheric turbulence, taking an average frame of the image sequence as a reference image, and taking each frame in the image as a floating image; generating a uniform grid control point matrix; generating an image deformation field by adopting B-spline non-rigid transformation; the floating image is transformed according to the deformation field, and normalized square difference between the floating image and the reference image is carried out to serve as a target function of image registration similarity; solving an optimal control point matrix when the target function is minimum by using an adjustable exponential damping factor LM algorithm fused with a particle swarm algorithm; and obtaining a registered floating image according to the optimal control point matrix. When the method is used for processing multiple frames of distorted turbulence images, the stability is relatively good, and relatively good image correction quality can be obtained.

The invention discloses an image self-adaptive defogging method. The implementation structure comprises an image sensor module, an image self-adaptive defogging module and a general video transmissioninterface module. According to the invention, an image sensor is used for processing collected data through an image self-adaptive defogging module, and encoding and outputting are carried out according to a general video transmission format. The image self-adaptive defogging module can automatically judge input image data, automatically determine whether a scene needs defogging or not, automatically delineate a sky area and execute defogging operation on a pixel area needing defogging. According to the method, the self-adaptive defogging function can be integrated into the equipment, so thatthe capability of the target equipment for collecting information in a foggy scene is improved, and richer original information is provided for subsequent digital image processing.

The invention relates to the technical field of digital image processing, in particular to a local re-coloring algorithm based on image segmentation, which comprises the following steps of: 1, selecting an image to be processed; 2, marking a rectangular area, and enabling the target area to be contained in the rectangular area; 3, executing an image segmentation algorithm to obtain an initial alpha mask of the target area; 4, performing bilateral filtering processing on the initial alpha mask of the target area, and performing binaryzation to obtain a final alpha mask of the target area; 5, the final alpha mask of the target area is input into the image for superposition, and then the image target area can be segmented; 6, inputting the image target area into an image re-coloring algorithm; 7, obtaining an RGB color convex hull and a corresponding RGBA layer; 8, moving the peak of the RGB color convex hull to change the color of the corresponding image layer, and obtaining a re-colored image target area; and 9, overlapping to obtain a local re-colored image. According to the invention, local re-coloring can be well realized.

The present invention provides a method of lowering intraocular pressure which comprises administering a therapeutically effective amount of a pharmaceutical composition comprising 4-bromo-5-(2-imidazolin-2-ylamino)benzimidazole, or a salt thereof to the affected eye of a patient, as a single dose, wherein the affected eye has an intraocular pressure less than the baseline.

The invention discloses a module type multilayer composite acoustic-voltaic meta-material comprising a sheet-shaped acoustic-voltaic module. The acoustic-voltaic module comprises a base layer, a cavity layer and a neck layer which are sheet-shaped and closely arranged in turn. The base layer comprises a substrate base material and acoustic-electric energy converters which are arranged on the substrate base material. The cavity layer comprises an intermediate layer base material and cavity holes which penetrate through the intermediate layer base material. The neck layer comprises a neck layer base material and neck holes which penetrate through the neck layer base material. The acoustic-electric energy converters, the cavity holes and the neck holes are corresponding in arrangement in a one-to-one way. An independent Helmholtz resonator hole is formed by one corresponding group of the acoustic-electric energy converter, the cavity hole and the neck hole. All the Helmholtz resonator holes are divided into N structural types according to the shape and size of the Helmholtz resonator holes. The module type multilayer composite acoustic-voltaic meta-material has advantages of being miniaturized, modularized, integratable and easy to process so that the module type multilayer composite acoustic-voltaic meta-material is the base material capable of realizing acoustic pressure amplification of N frequencies and synchronizing acoustic-electric conversation of multiple frequency acoustic waves under the condition of Helmholtz resonance.

The present invention provides a method of lowering intraocular pressure which comprises administering a therapeutically effective amount of a pharmaceutical composition comprising 4-bromo-5-(2-imidazolin-2-ylamino)benzimidazole, or a salt thereof to the affected eye of a patient, as a single dose, wherein the affected eye has an intraocular pressure less than the baseline intraocular pressure for at least eight (8) hours.

The invention discloses an improved compressed sensing face recognition method, which includes step 1 image preprocessing; adopting a cumulative distribution function to perform histogram equalization on a gray-scale face image, and then adopting an LBP rotation-invariant uniform mode to extract a gray-scale face The face image feature vector constructs the LBP feature space; Step 2 finds the neighbor samples of the test image in the low-dimensional LBP feature space; Step 3 uses the neighbor samples to adaptively construct a redundant dictionary to complete the perceptual recognition of the test image. This method looks for the neighbor samples of the test sample in the low-dimensional LBP feature space, and the complete redundant dictionary is formed by the neighbor samples, the number of dictionary atoms is greatly reduced, and the dictionary atoms and the test samples have higher structural similarity, so the algorithm improves Recognition speed, and improve the correct recognition rate.

The invention discloses a vBM3d-based magnetic resonance image reconstruction method, which comprises the following steps of 1) acquiring k space data of a sample object by adopting a magnetic resonance coil, rearranging the k space data to obtain time-averaged k space data, and performing coil sensitivity calculation by utilizing the time-averaged k space data to obtain a sensitivity graph, 2) carrying out downsampling on the k space data, and rearranging the k space data according to an acquisition time sequence, and 3) performing magnetic resonance image reconstruction by using the down-sampled k space data obtained in the step 2) and the sensitivity graph obtained in the step 1) as input parameters of a vBM3d-based SENSE dynamic magnetic resonance image reconstruction model. According to the method, the problem of poor image quality during high-power down-sampling of a traditional SENSE reconstructed magnetic resonance image is solved, the reconstructed image quality is high, and the application range is wide.