632results about How to "Improve fusion effect" patented technology

The invention relates to the technical field of information, and particularly discloses a method for integrating and exchanging data on the basis of unique identification. The method includes building data element management models for business required to be integrated, exchanged and shared, and uniquely identifying each data item in each data element management model; mapping the identification in the data element management models with fields of multi-source heterogeneous databases; generating corresponding target SQL (structured query language) statements according to the fields corresponding to the identification; accessing the multi-source heterogeneous databases, executing the target SQL statements and returning result sets; fusing and processing the result sets by the aid of fusion algorithms. The method has the advantages that conflict examples in heterogeneous data sources can be effectively recognized and fused by the aid of the method, and accordingly data integration / data fusion effects can be improved on high level; the data exchange and integration accuracy can be effectively improved, and the data integration and exchange efficiency can be greatly enhanced.

The invention discloses a liver multi-phase CT image fusion method which comprises the steps of firstly performing coarse registering on a source image sequence according to a multi-resolution CT image registering method based on a combined histogram, then realizing automatic liver image dividing according to a region growing algorithm in combination with confidence connection and liver image dividing based on a gradient vector flow snake model, and effectively extracting the edge information of the liver; performing blood vessel extraction based on a directional region growing algorithm on the liver image, performing free deformation transformation based on a B spline and liver non-rigid registering based on space weighting mutual information on a liver essential image, thereby accurately finding an image pair at a same position of a space; and finally performing image fusion based on wavelet transformation. The liver multi-phase CT image fusion method aims at the characteristics of a liver CT image. An image separation process and an image registering process are combined with the image fusion process, thereby greatly improving fusion precision.

The invention discloses a health product for increasing bone density and a preparation method of the health product. Chinese dwarf cherries, Chinese herbal medicine extracts refined by adopting a modern extraction technology and other raw materials having the function of increasing the bone density are scientifically compounded and are scientifically combined omnibearingly to play a synergistic effect, so as to effectively promote the calcium absorption in multiple aspects, repair and reconstruct the cartilago articularis, promote the generation of synovial fluid, promote the synthesis of collagen in cartilago articularis substrates, prevent the further degradation of cartilage, indirectly reduce the osteoclast function, inhibit the re-absorption of bones, increase the content of bone calcium and perfect the biomechanical properties of the bones, so that the product has a good function of increasing the bone density. A microwave drying technology in the preparation method can be used for further improving the integration and biological stability of the health product, and by means of the antioxidant activity of a grape seed extract in the raw materials, the strong adsorption and inclusion functions of modified dietary fibers and the antifungal propertie of the Chinese herbal medicine extracts, an efficient, safe, nutritional and stable health product having the function of increasing the bone density is prepared finally.

Lipid assemblies, such as liposomes, comprising transfection enhancer elements (TEE's), which are complexed with the lipid assemblies by means of ionic interactions, or lipids incorporating such TEE's are disclosed for enhancing the fusogenicity of the lipid assemblies. The TEE's have the formula:hydrophobic moiety-pH sensitive hydrophilic moiety  (II)The pH sensitive hydrophilic moiety of each TEE is a weak acid having a pka of between 2 and 6 or a zwitterionic structure comprising a combination of acidic groups with weak bases having a pKa of between 3 and 8. Lipids incorporating one or more such TEEs have the formula (I):Lipid moiety-[Hydrophobic moiety-pH sensitive hydrophilic moiety]  (I)

The invention discloses an image processing method and system based on bi-sensor imaging, comprising the steps of conducting image processing on a first image and obtaining a first grey-scale map; conducting image processing on a second image, and obtaining a second grey-scale map; obtaining the current imaging distance when the first image and / or the second image are / is imaged; determining the target registering parameter based on the registering database and the current imaging distance; conducting position registering on the first grey-scale map and the second grey-scale map based on the target registering parameter, and obtaining a first registering image corresponding to the first grey-scale map and a second registering image corresponding to the second grey-scale map; erging the first registering image with the second registering image and displaying the two registering images. The invention also discloses a corresponding image processing system, comprising an imaging module, animage processing module, a registering module, and a merging display module. The invention is advantageous in that the influence of different imaging conditions on the registering of images can be taken into consideration; the registering precision can be improved, and the merging effect of images can be enhanced.

The invention belongs to the technical field of edge cloud computing systems, and discloses a distributed edge cloud system architecture. The architecture comprises an edge node, an edge computing intelligent brain platform layer and an edge security boundary layer, wherein the edge node communicates with the edge computing intelligent brain platform layer through an edge private network; an intelligent brain platform of the edge computing intelligent brain platform layer is in butt joint with a plurality of different edge nodes to realize distributed deployment; data are acquired through external terminal equipment accessed by the edge node and uploading the data to the edge node for processing; the edge computing intelligent brain platform layer communicates with the center cloud or theindustry cloud through the edge security boundary layer; the edge security boundary layer serves as an interface for communication between the edge cloud system and the center cloud or the industry cloud and is used for guaranteeing the communication security between the edge cloud and the center cloud or the industry cloud; the system architecture has the characteristics of low time delay and high security, and meets the requirements of agile connection, real-time service, data optimization, intelligent application, security and privacy protection.

Provided is a back sheet for a solar battery which holds an excellent gas barriering property and which is excellent in a weatherability and a light shielding property.It is a back sheet for a solar battery comprising a light shielding colored layer and a weather resistant polyester base resin layer and comprising a gas barriering layer containing a weather resistant coating layer and an inorganic thin film layer provided between the above layers, wherein the weather resistant coating layer comprises at least one selected from (a) a cross-linked product of polycaprolactonepolyol and / or polycarbonatepolyol, (b) a cross-linked product of modified polyvinyl alcohol and (c) an acryl base copolymer having at least one group selected from the group consisting of a UV ray stabilizing group, a UV ray absorbing group and a cycloalkyl group.

The invention brings forward an aerial photography image and geographical data splicing method based on ORB feature matching. The method comprises the following steps: step 1, reading images to be spliced and geographical information; step 2, distributing tasks to processors; step 3, extracting ORB features of the images to be spliced; step 4, performing initialization estimation on parameters of a camera shooting the images to be spliced and solving a rotation matrix; step 5, improving estimation precision by use of bundle adjustment; step 6, performing initial splicing on the images to be spliced; step 7, performing brightness increment compensation on the images after the splicing, and based on multiband fusion of an image pyramid, performing conditional interpolation fusion on the geographical information after the splicing to obtain splicing result images; and step 8, and performing primary integrated splicing fusion on the splicing result images processed through all threads of each processor, and performing merging to obtain a final result image.

Disclosed is a rubber process oil in which the content of polycyclic aromatics (PCAs) as determined by the IP 346 method is less than 3% by mass and which is rich in aromatic hydrocarbons, and a method for producing the same. The aniline point of the rubber process oil is 80° C. or less, and the % CA value as determined by ring analysis according to the Kurtz method is from 20 to 50%. The rubber process oil is produced by using extraction of lube oil fraction with a solvent having a selective affinity for aromatics. The extraction conditions are determined so that the extraction yield is regulated to a predetermined requirement defined by the PCAs content of the lube oil fraction. Alternatively, the extract is cooled to further separate into the extract and the raffinate, and the second raffinate is used for the rubber process oil.

This invention relates to a method for interfusing fuzzy images based on region characters including the following steps: 1, applying small wave frames to carry out multi-dimension resolutions to being interfused images to get a series of high frequency components and a lowest component, 2, carrying out K average clustering to the low frequency part of the infrared images and dividing it to three kinds, 3, expressing the three kinds to an important target region, a second important region and a background region to make a decision to the interfusion based on the fuzzy region character and measurement target of the HF part of a sensor multi-image, 4, sending the final multi-resolution images into a filter made up of a same small wave basic function to be filtered and summing up the filtered image signals, lowering the transformation layer number of the small wave frame by one, carrying out a process of the fall-sample to the filter then to transform the next layer inversely and repeating the process till finishing the inverse transformation to the entire wave frames to get a final fused image.

An infrared and visible light video fusion method based on moving target detection belongs to the technical field of video fusion. A moving target is detected through low-rank sparse representation, the target is extracted using the low-rank and sparse time slices along X-T and Y-T planes, the integrity of the target detected is ensured by spatial information, and the robustness and accuracy of detection are improved. Then, the structure information of an image can be better described through non-subsample shearlet transform with a good fusion effect. The method has the advantages of high computational efficiency, unlimited filtering direction, translational invariance, and the like, and improves the fusion effect. In addition, the low-frequency sub-band coefficients are fused according toa sparse representation rule, the high-frequency sub-band coefficients are fused according to a weighting rule taking a target saliency map as a weighting factor, and a better fusion effect is achieved. Therefore, the infrared and visible light video fusion method based on moving target detection presented by the invention is more robust, and has a better fusion effect.

The invention discloses an image fusion method based on an imaging mechanism and non-sampled Contourlet transform. The method comprises the following steps of: first, carrying out the multi-scale and multi-direction decomposition to a source image and obtaining sub-band coefficients of different frequency domains via the non-sampled Contourlet transform; next, building a fusion rule based on the direction vector norm to the low frequency sub-band coefficients and building a fusion rule based on the union of the local directional contrast and the direction vector standard deviation to the band-pass direction sub-band coefficients; then, respectively combining the low frequency sub-band coefficients of the source image and each band-pass direction sub-band coefficients according to the built fusion rules and obtaining the non-sampled Contourlet transform coefficients of the fusion images; finally, rebuilding the fusion images via the non-sampled Contourlet inverse transform. The invention has the advantages of good fusion effect, little infection of the registration error on the fusion capability and being capable of effectively avoiding transferring the noise to the fusion images, and is applicable to the subsequent treatments and the image displays of the imaging systems.

The invention discloses a honeypot defense method and system based on mimicry defense, equipment and a medium, which are applied to the technical field of network security. A virtualization managementsubsystem comprises a mirror image management module, a honeypot management module, a virtual network management module and a control scheduler which are connected in sequence, the mirror image management module constructs a mimicry honeypot mirror image through a KVM virtual machine mirror image technology, a plurality of virtual high-interaction honeypots and a mimicry honeypot system are obtained, and the honeypots are mimicry honeypots; the honeypot management module manages the honeypots and monitors the state of the honeypots; the virtual network management module controls the honeypotsystem to perform data access and network communication; and a control scheduler dynamically switches the mimicry honeypots and the network according to the output judgment result of the mimicry honeypots. According to the invention, mimicry defense is combined with the honeypot system, so that the security and controllability of network space security defense are improved.

The invention provides a multi-exposure image fusion method based on an end-to-end deep learning framework. The method comprises steps as follows: a parameter theta is obtained through training; an original image is subjected to fusion processing on the basis of a convolutional neural network, and an output image is obtained; the original image is subjected to N downsampling, and N<2> original sub-images are obtained; the N<2> original sub-images are subjected to fusion processing respectively on the basis of the convolutional neural network, and N<2> output sub-images are obtained; the N<2> output sub-images are combined, and a combined sub-image is obtained; the output image and the combined sub-image are subjected to weighted average, and a result fusion image is obtained. On the basis of the deep learning framework, one end-to-end multi-exposure image fusion method is realized, the defect that a traditional method is just used for calculating fusion coefficients through the network is changed, and the complexity of the algorithm is greatly reduced.

The invention relates to the technical field of image processing, and discloses an intelligent group photo taking method and device, electronic equipment and a storage medium, and the method comprisesthe steps: responding to a group photo taking instruction inputted through a photographing operation interface, obtaining a photographed first image, and obtaining reserved region information specified for a to-be-group-photo target in the first image through the photographing operation interface; in response to a sending instruction input through the shooting operation interface, sending a groupphoto request to a background server, the group photo request comprising the first image and reserved area information; and receiving a group photo image sent by the background server, wherein the group photo image is obtained by fusing a target image corresponding to the target to be subjected to group photo taking into the first image by the background server according to the reserved area information, and the target image is extracted from a second image containing the target to be subjected to group photo taking. According to the technical scheme provided by the embodiment of the invention, the operation is simple, the image synthesis speed is high, and the group photo image fusion effect is good.

The invention discloses an image generation device and method. The device includes a first acquisition unit for acquiring a black and white image and a color image of the same acquisition object; a second acquisition unit for respectively performing image processing on the black and white image and the color image to obtain the black and white image information of the black and white image and the color image information of the color image; a determination unit for combining the black and white image information and the color image information to determine the fusion weight of the black and white image and the color image; and a fusion unit for fusing the black and white image information and the color image according to the fusion weight to generate a fusion image. According to the invention, the black and white image and the color image can be fused, the fusion value is a value determined based on the image information of the black and white image and the color image instead of a fixed value determined in advance, and because the fusion weight of different images is dynamically determined according to the image itself, the image fusion effect and the fusion image quality are further improved.

The invention belongs to the technical field of batteries, in particular to an integrated all-solid-state lithium metal battery, including the positive electrode, a negative electrode and an organic-inorganic composite solid electrolyte disposed between the positive electrode and the negative electrode, the negative electrode is made of metal lithium, the organic-inorganic composite solid electrolyte comprises polyethylene oxide, an electrolyte and ceramic nanowires uniformly dispersed in the polyethylene oxide, and an adhesive in the positive electrode comprises a mixture of the polyethyleneoxide and the electrolyte. Compared with the prior art, the organic-inorganic composite solid electrolyte with high ionic conductivity and high mechanical strength can be obtained by uniformly dispersing ceramic nanowires in polyethylene oxide (PEO); Furthermore, the binder in the cathode contains the mixture of polyethylene oxide and electrolyte, which effectively ensures the ion transport in the cathode and the good contact of the interface, so as to obtain the integrated all-solid-state lithium metal battery with high safety and excellent electrochemical performance.

The invention belongs to technology field of carrier material for non-viral gene transfection, and relates to a carrier material for non-viral gene transfection, plasmid DNA compound particle and preparation method and administration. The weight ratio of polyethylene imine and hydrophobic unit containing benzene ring is 1:9-4:6.The polyethylene imine is superbranched polyethylene imine (PEI) with average molecular weight of 1.8K-25K.The hydrophobic unit containing benzene ring is one or more of gamma -benzyl-L-glutamic acid, epsi -carbobenzoxy lysine and phenylalanine at any ratio. The water soluble polyethylene imine modified substance of hydrophobic unit containing benzene ring can compound with genic material to form a particle with positive charge on surface and particle diameter of 50-300nm.The compound particle can transfer loaded genic material into cell to realize expression of genic material and complete transfection process. The invention prepared non-gene transfection carrier material has the advantages of low toxicity and high up transfection efficiency; and can be used as transfection agent in vivo and in vitro.

The invention discloses a super-resolution reconstruction method based on feature fusion of dual-channel convolution network, which comprises the following steps: a dual-channel convolution network isbuilt based on dense convolution network of different convolution cores; The dual channel convolution network comprises: two sub-channels, each sub-channel adopts the structure of dense connection network, the structure is generated by cascading a plurality of dense connection blocks, each dense connection block is composed of a 1* 1 convolution layer, a 3 *3 convolution layer and a hop layer connection, and a PRELU layer is used as a nonlinear activation function in front of each convolution layer; The weighted L1 norm is used as the loss function. After each sub-channel, the image is reconstructed with super-resolution, and the loss function is calculated and the parameters of the model are optimized. The loss function is the weighted sum of the calculated loss function of the sub-channel output image and the calculated loss function of the whole output; Input any size of low-resolution image, load the trained model, and output the reconstructed high-resolution image.

This invention relates to a merge method for multiple sensor images based on an optimum small wave filter set, which applies small waves to carry out multi-dimension dissolution to the being merged images to get a series of HF components and a lowest frequency component, then applies a character pick up method based on the visual property to the HF part for merging and applies the weighted average method to merge the low frequency part to get the merged image by small wave inverse transformation to the merged results, finally applies the smallest mean-root-square error to evaluate the merged images and carries out optimized search to small coefficient taking the pass-band energy and the non-pass band energy of the small filter coefficient so as to get the optimum design of the small filter set.

The invention discloses an infrared polarization image fusion method based on the Laplacian pyramid. The method is mainly used for fusion of an infrared radiation intensity image and a polarization degree image. By means of the method, Gaussian pyramid decomposition can be carried out on each image to be infused so as to acquire all levels of an approximate Gaussian pyramid and all levels of the Laplacian pyramid of the image, image fusion is carried out on the top layer of the approximate Gaussian pyramid through the weighted average method, image fusion is carried out on all layers of the Laplacian pyramid with a local area average gradient as a criterion, and image reconstruction is carried out on an infused image to acquire a final infused image. The implement method is simple and high in arithmetic speed, and testing shows that the infused image is improved a lot when compared with the infrared radiation intensity image and the polarization degree image.

The invention discloses a heavy oil modifying method which comprises the following steps: mixing a heavy oil raw material with a homogeneous catalyst, and mixing with a supercritical hydrogen supply solvent, wherein the content of the hydrogen supply solvent in the heavy oil raw material is 50 mug / g-5wt%; and in the presence of hydrogen, carrying out heavy oil hydrocracking reaction on the mixture of the heavy oil raw material, the catalyst and the hydrogen supply solvent under certain reaction conditions. In the heavy oil modifying method, suspension bed hydrocracking and supercritical treatment are organically combined, and the respective advantages are given full play to achieve the effect of synergic cooperation, thereby reducing the coking tendency, enhancing the impurity removal capacity and also enhancing the operational stability of the suspension bed hydrocracking.

The invention discloses a line structured light vision measuring system complete calibrating method comprising scanning direction information, and belongs to the line structured light vision system calibrating method field. The line structured light vision measuring system complete calibrating method comprises the steps that based on a help of a relative motion calibrating device of a straight line slide rail system, by combining with a motion coordinate system conversion thinking, a routine light plane calibrating process is directly used to acquire a plurality of opposite relative motion calibrating images comprising light strip position information and scanning direction information at the same time by one time, and therefore calibrating steps are simplified, and at the same time, a calculation amount required by solving a structured light plane space equation of a calculation system is greatly reduced. The line structured light vision measuring system complete calibrating method is advantageous in that a scanning direction vector equation is solved and fitted accurately, and the scanning direction can be any direction, and at last, the completer line structured light vision measuring system calibrating method comprising a vector scanning step is defined and determined again. The line structured light vision measuring system complete calibrating method has double effects of improving calibrating efficiency and reducing calibrating errors.

The invention discloses a self-adaptive fusing method of an infrared polarization image based on wavelets. The self-adaptive fusing method comprises the following steps of: carrying out wavelet decomposition on an input image and establishing respective wavelet decomposition coefficient; respectively calculating a matching measure of respective high-frequency component of the input image; calculating a decision-making module part of the fusing method by combining a genetic algorithm; carrying out self-adaptive optimization on a key parameter threshold value T in a decision-making factor by utilizing the genetic algorithm; calculating the high-frequency component of a fusion image; carrying out average weighting by utilizing a low-frequency component of a source image to obtain the low-frequency component of the fusion image; and combining the high-frequency component with the low-frequency component and utilizing wavelet inverse transformation to obtain the final fusion image. According to the self-adaptive fusing method disclosed by the invention, the fusing effect of the infrared polarization image is obviously improved.

The embodiment of the invention provides a data fusion and target detection method, device and equipment, and the method comprises the steps: obtaining an image and point cloud, and respectively determining a corresponding pixel point, projected to the image, of each point in the point cloud as a projection image pixel point; inputting the pixel values of the projection image pixel points into a dimension prediction model; obtaining image features of the target dimension, wherein the target dimension is the dimension adapted to the point cloud; carrying out dimension splicing on the image features and the point cloud; therefore, in the first aspect, the scheme for fusing the image and the point cloud is provided; in the second aspect, the image feature output by the dimension prediction model is the image feature matched with the dimension of the point cloud, the image feature and the point cloud are fused, and the fusion effect is improved.

The invention discloses a heavy-load grinding wheel. The heavy-load grinding wheel comprises the following components in percentage by weight: sintered corundum, fused alumina zirconia, brown fused alumina, a coupler, phenol-formaldehyde resin powder, elastic polyvinyl chloride powder, cryolite powder, light calcium carbonate micro powder and impregnation chopped glass fibers and is prepared by a hot pressing molding process. The elastic polyvinyl chloride resin powder is mixed in a grinding material, so that the tenacity and the shock absorbing effect of the grinding wheel are improved, and the probability of sheet blasting is greatly reduced. On the other hand, elastic polyvinyl chloride has excellent flame resistance, so that burning of grinding heat to phenol-formaldehyde resin is reduced, the bonding ability of the phenol-formaldehyde resin to the grinding material is improved, and the grinding ratio of the grinding wheel is improved. The coupler is used for modifying the surface of the phenol-formaldehyde resin, so that the interface bonding force between the organic resin and the inorganic grinding material is stronger, and the rotation strength of the grinding wheel is improved. Furthermore, due to the adoption of the impregnation chopped glass fibers, the dissolving ability of the phenol-formaldehyde resin is favorably enhanced, and the rotation strength of the grinding wheel is further improved.

The present invention discloses a PRCA-based NSST image fusion method. The method comprises the following steps of S1, respectively subjecting to-be-fused images to multi-scale decomposition by using a non-down-sampling redundancy lifting non-separable wavelet (RLNSW), completing the directional localization and then obtaining the low-pass sub-band components and the band-pass sub-band components of the to-be-fused images; S2, fusing the low-pass sub-band components of the to-be-fused images based on the first fusion rule of the robust principal component analysis (RPCA), and fusing the band-pass sub-band components of the to-be-fused images based on the second fusion rule of the robust principal component analysis (RPCA); S3, after the fusion process of the step S2, subjecting the low-pass sub-band components and the band-pass sub-band components of the to-be-fused images to inverse NSST conversion, obtaining a fused image and outputting the image. The method is simple in implementation, good in image fusion effect, short in consumed time and good in practicability.

The invention relates to a discriminative dictionary learning based multi-source image fusion denoising method. The method includes: acquiring multi-source images as training samples, and learning thesamples through a K-SVD algorithm to obtain an initial cartoon dictionary and an initial texture dictionary, introducing weighting nuclear norm constraint to bring forward a new dictionary learning model, performing new dictionary learning model learning to obtain a cartoon dictionary and a texture dictionary, decomposing to-be-fused images through an MCA algorithm to obtain a cartoon component and a texture component, introducing weighting Schatten sparse nuclear norm constraint to the cartoon component, adding grey level histogram gradient protection to the texture component to bring forward a new image decomposition model, iterating the model to obtain a cartoon sparse coding coefficient and a texture sparse coding coefficient, respectively fusing to obtain a cartoon component and a texture component according to a principle of maximum sparse coding coefficient l1 norm values of corresponding components, and adding the cartoon component and the texture component to obtain a final fusion image. The method has advantages that image fusion and denoising are realized, false information transferring is avoided, time consumption is reduced, and fusion and denoising performances are improved.

A fixing device includes, a belt, and a plate. The belt has a first surface and a second surface opposite to the first surface. The plate is made of metal and has a sliding surface that is configured to slide on the first surface of the belt in a predetermined direction. The sliding surface of the plate has roll marks that extend along the predetermined direction.

The invention relates to an image fusion system based on a low-light and infrared sensor. The system is divided into a low-light and infrared sensor information acquisition module, an FPGA core processing module, a DSP co-processing module and an output display module; video images collected by the external low-light and infrared sensor are input to a device through an interface; the input video images are subjected to image preprocessing including image denoising, image enhancement and image registration, wherein image denoising and image enhancement are low in delay requirement and are achieved in an FPGA chip, the computation amount required for an image registration algorithm is large, and image registration is achieved in a DSP chip; the pre-processed video images are fused through the FPGA chip, wherein grayscale fusion and pseudo-color fusion are included; an FPGA control logic can select one path of images to be output through the interface, wherein one path of images include asingle low-light video, a single infrared video, a grayscale fused video and a pseudo-color fused video. The image fusion system is high in precision, low in delay and good in expansibility and has important practical significance on nighttime observation and exploration application.