61 results about "Quantum image" patented technology

The invention discloses a chip surface defect visual detection method and system, and the method comprises the steps: carrying out the high-sensitivity imaging through the dynamic adaptation of a quantum imaging enhancement module to the surface reflectivity, and achieving the sparse efficient processing of a defect signal through the combination of event-driven vision and a pulse neural network; based on a risk thermodynamic diagram generated in real time, intelligently scheduling detection precision and speed resources, and utilizing multi-modal feature decoupling and a federal knowledge graph to accurately associate defects and process roots; the digital twinning module synchronously predicts a defect evolution path and drives online adjustment and optimization of process parameters, and meanwhile the dynamic compensation module corrects optical defocus in real time. According to the invention, full-detection coverage of nanoscale defects is realized, a defect transfer chain is actively blocked while the detection efficiency is improved, and the chip manufacturing yield and reliability are remarkably improved.

The invention discloses an image classification method, system and device based on a quantum convolutional neural network, a medium and a product, and relates to the field of image classification, and the method comprises the steps: obtaining a to-be-classified image; preprocessing the to-be-classified image to obtain a processed to-be-classified image; converting the processed to-be-classified image into quantum image information by using a quantum coding technology; determining the category of the to-be-classified image by using an image classification model according to the quantum image information; wherein the image classification model is obtained by training a quantum convolutional neural network by using a training data set; the quantum convolutional neural network comprises a quantum entanglement layer, a quantum convolutional layer, a quantum pooling layer and a quantum full-connection layer which are connected in sequence. According to the method, the quantum convolutional neural network is adopted to classify the images, quantum entanglement and superposition characteristics are fully utilized, and the classification performance and the overall precision of the network are effectively improved.

The invention provides a focusing optimization method, device and equipment based on quantum deep learning. The method comprises the following steps: acquiring a continuous shooting image sequence of a target object; the method comprises the following steps: shooting a target object by using photographic equipment to obtain a continuous shooting image sequence; quantum image features corresponding to the continuous shooting image sequence are extracted; wherein the quantum image features comprise quantum bits, quantum dynamic trajectories and quantum depth-of-field distribution; inputting the quantum image features into a pre-trained quantum neural network to obtain a focus prediction result of the target object; and adjusting the focal length of the photographic equipment according to the focus prediction result. Through the above method, the focusing speed and precision are improved, so as to meet the shooting requirements in ultra-high-speed photography and complex scenes.

The application discloses a quantum image multiplication operation method and device and electronic equipment, and relates to the field of quantum operation, and solves the problem of low performance of a quantum image multiplication operation algorithm in the prior art, and the technical solution points are as follows: a plurality of quantum images with shared position information and in a superposition state are prepared based on a NEQR quantum image representation model; any two quantum images in the plurality of quantum images are subjected to multiplication operation processing based on a quantum multiplier, and a matrix of pixel values of the quantum image is obtained; information of each pixel point in the matrix of pixel values of the quantum image is extracted, and the information is converted into classical image information; wherein, the operation steps of quantum multiplication are improved according to binary multiplication, the quantum multiplication improved based on binary multiplication is designed by using a Toffoli gate and a quantum full adder, and a quantum multiplier is obtained. The application improves the performance of a quantum image expression algorithm, and makes it easier to simulate under a classical computer.

A method for imaging an object illuminated with natural light including arranging an optical filter in an optical path of at least a portion of the natural light that is reflected and / or refracted or scattered from the object; arranging an optical detector in an optical path of light at least one of reflected from and / or transmitted through the optical filter; detecting, using the detector, individual photons for a time period to provide a times series of individual photon events; segmenting the time series into a plurality of bins; determining a number of detected photons within each bin to provide a time series of photon counts per bin; replacing and / or reconfiguring the optical filter a plurality of times followed by detecting, segmenting and determining to obtain a plurality of times series of photon counts per bin; and forming an image of the object based on the plurality of times series.

A quantum method that uses the Mz quantum circuit that receives a given single chaotic value to generate strong quantum key stream of three keys. The method includes encrypting a quantum plain color image; applying set of CNOT gates between qubits of a quantum image and qubits of a quantum key to obtain a quantum encrypted image; generating a new quantum key, applying additional set of CNOT gates between the qubits the quantum color image, and the corresponding qubits of the quantum key as target qubits; performing a quantum plain scrambling (QPS) operation; and applying set of CNOT gates; and obtaining, by the quantum circuit, a quantum ciphered image.

The invention discloses a quantum image sensing method and device based on exposure modulation. The sensing end performs frame-by-frame exposure modulation on the same scene in continuous K frames, and regulates and controls the expected number of incident photons of each frame; the pixels output a 1-bit binary image in each frame and obey Poisson distribution. And the collection end takes K frames as a group to carry out maximum posteriori estimation to obtain reference intensity estimation of each pixel. In order to improve robustness and speed, an RED-PRO iterative algorithm based on FISTA acceleration is adopted in the reconstruction process, after gradient descent of a data consistency item, the data is projected to a pre-training de-noising device manifold, and a pixel adaptive step length is given based on Fisher information. According to the method, the signal-to-noise ratio is remarkably improved and artifacts are inhibited in a scene with low illumination, saturation and limited dynamic range, the 1-bit sensing circuit architecture does not need to be changed, and the existing QIS / SPAD sensor and the lens module can be compatible only through exposure modulation and software reconstruction.

The invention discloses a multi-bit quantum image sensor based on single photon detection and a hardware system, and belongs to the technical field of quantum image sensors. The quantum image sensor comprises a photon detection array; each pixel in the photon detection array corresponds to one quantum response unit; an avalanche trigger circuit in the quantum response unit is used for detecting avalanche current caused when a photon detection unit detects photons and outputting a digital trigger signal; the quenching circuit is used for quickly terminating current after avalanche; the photon counting unit is used for counting the number of photon events within specified exposure time; and the multi-bit quantization unit is used for performing quantization coding on the photon count value based on the statistical characteristics of the photon events. According to the scheme, a hardware integrated processing architecture from quantum image acquisition to image reconstruction is formed, and the imaging effect of image reconstruction based on data acquired by the quantum image sensor is improved.

The invention provides a power equipment image processing method and system based on a quantum image coding algorithm. The method comprises the following steps: S1, acquiring a multi-modal image of power equipment; s2, preprocessing the multi-modal image to obtain standardized image data; s3, based on the structural characteristics of the power equipment, carrying out adaptive partitioning on the standardized image data to obtain a plurality of sub-image blocks, and mapping the pixel information of each sub-image block into quantum state information through angle coding; s4, calling a quantum image coding algorithm, initializing a quantum circuit, generating an optimal quantum circuit by taking fidelity maximization of an output state of the quantum circuit and a quantum state of a target sub-image block as a target, and extracting hidden space quantum state characteristics of each sub-image block based on the optimal quantum circuit; and S5, fusing the hidden space quantum state features of all the sub-image blocks by adopting a quantum state direct product mode, constructing a global feature quantum state, and inversely converting the global feature quantum state into classical enhanced image data through a quantum decoder.

The invention provides an adaptive coincidence gate width optimization quantum imaging method based on a scattering free path. Firstly, pump light pumps a PPKTP crystal, and an entangled photon pair is generated through the SPDC process; then, separating the photons by using a PBS (Phosphate Buffer Solution), transmitting the photons along a reference light path and a signal light path containing a scattering environment respectively, and acquiring a photon arrival time sequence by a corresponding detector; thirdly, simulating a transmission process of signal photons in a scattering environment based on a Monte Carlo method, calculating a total scattering free path, counting the number of photons of each pixel point under different scattering times, and further screening out the optimal scattering times with the maximum number of photons; then, calculating a delay inequality according to a minimum total scattering free path corresponding to the optimal number of scattering times, and determining a self-adaptive coincidence gate width in combination with a fluctuation range of the total scattering free path; and finally, correcting a signal photon arrival time sequence by using the delay inequality, completing pixel-by-pixel coincidence counting based on the corrected time sequence and the coincidence gate width, and obtaining a quantum grayscale image through linear mapping.

This invention relates to the field of quantum imaging technology and proposes a digital phase-locked microwave magnetic field imaging system and method based on diamond NV centers. This invention images microwave fields based on the principle of power-broadened magnetic resonance. The system consists of multiple subsystems: an excitation optical path, an imaging optical path, an acquisition system, and a bias magnetic field. The excitation light is used to excite the diamond NV centers; the imaging optical path captures the fluorescence changes during microwave exposure; the acquisition system controls the testing system and analyzes data through a programmed host computer; and the bias magnetic field splits the resonance peaks to increase the bandwidth of the measured microwave field. Furthermore, imaging at different resolutions can be achieved by changing the objective lens. This invention enables non-destructive, non-invasive measurement of microstrip lines at room temperature using the NV center ensemble, thereby analyzing their operating status. In practical applications, this method offers advantages such as high sensitivity and rapid imaging.

The application discloses an image classification method and related device, and the method comprises the steps of obtaining image features of an image to be classified; performing quantum state encoding on the image features based on a quantum feature encoder to obtain an IFRQI quantum state; performing quantum state evolution on the IFRQI quantum state obtained by quantum state encoding based on a variational quantum circuit; measuring the quantum state evolved by the variational quantum circuit to determine the image category of the image to be classified according to the evolved quantum state. Compared with the prior art, the application uses IFRQI technology to extract image data for encoding and feature extraction, which can effectively reduce the number of quantum bits required for encoding, and then uses a quantum variational circuit to realize image classification. For a 2 n ×2 n dimensional image, only 2n quantum bits are required to complete the quantum image representation task, thereby reducing the occupation of quantum computing resources and improving the efficiency of feature extraction and data processing.

The application provides a power equipment image processing method and system based on a quantum image coding algorithm, comprising the following steps: S1, acquiring a multi-modal image of power equipment; S2, preprocessing the multi-modal image to obtain standardized image data; S3, based on the structural characteristics of the power equipment, adaptively dividing the standardized image data into a plurality of sub-image blocks, and mapping the pixel information of each sub-image block into quantum state information through angle coding; S4, calling a quantum image coding algorithm, initializing a quantum circuit, taking the maximum fidelity of the output state of the quantum circuit and the target sub-image block quantum state as the goal, generating an optimal quantum circuit, and extracting the hidden space quantum state features of each sub-image block based on the optimal quantum circuit; and S5, fusing the hidden space quantum state features of all the sub-image blocks in a quantum state direct product manner to construct a global feature quantum state, and inversely converting the global feature quantum state into classical enhanced image data through a quantum decoder.

This invention relates to a quantum imaging system based on deconvolution that penetrates scattering media, belonging to the field of optical imaging. The invention addresses the problem of image distortion caused by interference from scattering media in quantum imaging. The system comprises a beam emitter, a beam receiver, and a scattering medium. The beam emitted by the beam emitter travels through the scattering medium to the surface of the imaging target, then reflects off the target surface and penetrates the scattering medium again. The echo beam is received by the receiving optics and used for imaging. First, the beam emitter uses a spatial light modulator to generate a point source beam, and the beam receiver obtains the point spread function of the quantum imaging system penetrating the scattering medium. Then, the beam emitter uses the spatial light modulator to generate an orbital angular momentum beam, and the beam receiver obtains the distorted image of the quantum imaging system penetrating the scattering medium. The point spread function and the distorted image are input together into a deconvolution module for calculation, reconstructing the target image hidden behind the scattering medium.

The application discloses an LSQb steganography method based on differential steganography, which comprises the following steps: performing differential steganography on a secret image, and expanding the obtained image; converting the obtained image and a cover image into a quantum image in NEQR form, and embedding information of the secret image into a predetermined area of the cover image; transmitting the transmission image to a receiving end by using TCP / IP; extracting the least significant bit of the gray value of each pixel of the image at the receiving end, converting the extracted NEQR image into a classical form image; finding the embedded area from the obtained image, compressing the image extracted from the area into the size of the secret image, and performing accumulation processing on the obtained image to restore the secret image. The application improves the concealment of the transmission secret image, and enhances the security and integrity of information.

The invention belongs to the technical field of quantum information, and relates to a non-detection photon imaging system based on a single optical fiber integrated nonlinear waveguide. Comprising a continuous tunable pumping laser source, an optical amplifier, an adjustable optical attenuator, a first beam splitter, a first adjustable optical delay line, a first polarization controller, a second polarization controller, a first optical circulator, a nonlinear straight waveguide, a second optical circulator, a first optical filter, a second optical filter, a third optical filter, a fourth optical filter, a third optical circulator, a second adjustable optical delay line and an optical absorption terminal. The system comprises a first light collimator, a first lens, a three-dimensional scanning platform, a second lens, a second light collimator, a second beam splitter, a third polarization controller, a fourth polarization controller, a first single-photon detector, a second single-photon detector and a coincidence measurement unit. Compared with a traditional non-detection photon imaging system, quantum imaging of a transparent object can be achieved only through half of resource expenditure, and robustness is provided for the imaging system through all-fiber integrated configuration.

The invention discloses an expressway accident vehicle positioning identification method based on quantum and unmanned aerial vehicle technologies, and relates to the technical field of quantum technology deep learning application, and the method comprises the steps: constructing a PPP-RTK model, introducing a TTTrack algorithm, and collecting expressway vehicle image information through an unmanned aerial vehicle based on the PPP-RTK model and the TTTrack algorithm; preprocessing the image; performing feature extraction on the image through a CNN (convolutional neural network) and an Xception classification model in sequence; judging whether the vehicle contained in the image is an accident vehicle or not according to the image; if the vehicle is in the accident, quitting the picture, and if the vehicle is in the accident, preparing a quantum image through an ONEQR model, processing the quantum image through a target detection algorithm, processing the image, and extracting vehicle features including the vehicle in the accident; and establishing a database according to the extracted vehicle features. According to the invention, the efficiency and precision of image processing are obviously improved, and the accuracy of image recognition is improved.

The application discloses a quantum correlation imaging system based on a microlens array, which comprises a transmitter, a receiver, a comprehensive control system and an image inversion system; a light source unit of the transmitter outputs a two-mode vacuum squeezed state, which is divided into a mode A light field and a mode B light field. The mode A light field remains in the local, and the mode B light field returns to the receiver after acting on a target, the receiver performs time synchronization and coincidence measurement on the mode A and B light fields under the transceiving synchronization control of the comprehensive control system, and delivers detection results to the image inversion system. The image inversion system inverts the intensity image of the target by using a high-efficiency data processing algorithm. The comprehensive control system is used for transmitter output control, receiver coincidence measurement control, clock synchronization and real-time communication. The application realizes a quantum imaging system with high energy collection efficiency, can be used for fast imaging of dark and weak targets in a strong background, and can also be applied to medical imaging of biological tissues with low damage threshold.

One or more embodiments of the present disclosure provide a multimedia conference data processing method based on an artificial intelligence model and related devices. The method includes: obtaining a plurality of first images of a first multimedia conference, and obtaining conference text of the first multimedia conference; performing sub-image extraction on at least one second image to obtain a plurality of sub-images; generating description information corresponding to the plurality of sub-images according to the conference text of the first multimedia conference; determining a source text for generating a conference minutes of the first multimedia conference by using a first artificial intelligence model, and generating the conference minutes of the first multimedia conference; and in response to the source text including first description information, determining a first sub-image according to an association relationship, and adding the first sub-image in the conference minutes of the first multimedia conference. In the method, the image information of a high-quality sub-image in the screen sharing content is understood, and the screen sharing content in the form of an image is added in the conference minutes.

The present application relates to image sensor, image processing technical field, for putting forward new image reconstruction method, obtains the image of removing motion blur, for this, the technical scheme that the present application adopts is, the image removing motion blur method for quantum image sensor, the block and image of input binary image sequence composition, patch-based optical flow algorithm realizes the alignment of block and image, based on the merging algorithm of incident photon number change with time realizes binary sequence merging, obtains the image of removing motion blur, wherein, the combination of multiple binary image sequences is called "block", the spatial window of pixel is called "patch", the sum of binary sequence in block is called "block and image". The present application is mainly applied to the design and manufacture occasion of quantum image sensor.

An image reconstruction system includes a single-photon detector array and a computing device. The single-photon detector array captures a time series of low-bit-depth image frames, which have a high temporal resolution (framerate). The computing device is configured to receive and process the time series of low bit-depth image frames to reconstruct a time series of high-quality reconstructed image frames. The image reconstruction pipeline leverages by the computing device incorporates a deep-learning-based, end-to-end neural network configured to reconstruct high-quality grayscale images from low bit-depth (e.g., 3-bit) quanta image data.

One or more embodiments of the invention provide a multimedia conference data processing method based on an artificial intelligence model and a related device, and the method comprises the steps: obtaining a plurality of first images of a first multimedia conference, and obtaining a conference text of the first multimedia conference; performing sub-image extraction on the at least one second image to obtain a plurality of sub-images; generating description information corresponding to the plurality of sub-images according to the conference text of the first multimedia conference; determining a source text used for generating a conference summary of the first multimedia conference by using the first artificial intelligence model, and generating the conference summary of the first multimedia conference; and in response to the first description information included in the source text, determining a first sub-image according to the association relationship, and adding the first sub-image in the conference summary of the first multimedia conference. In the method, the image information of the high-quality sub-image in the screen sharing content is understood, and the screen sharing content in an image form is added in the conference summary.

To provide an image filter device that applies filter processing to a classical image compatible with a quantum image so as to reduce the noise caused by the quantum image.SOLUTION: An image filter device 1, 7 applies filter processing to an input image or an output image so as to reduce the noise generated in the output image due to a state of a quantum image, in the case where the input image, which is a classical image, is encoded to form the quantum image and the output image, which is a classical image, is decoded by a result of measuring the quantum image. Encoding to form the quantum image includes basis encoding by associating position information in the classical image with each of multiple bases. The filter processing includes image sharpening by defining neighborhoods of each pixel position on the classical image in basis-encoded state.SELECTED DRAWING: Figure 1

The invention discloses a wood detection method and system based on a quantum image enhancement algorithm, and relates to the technical field of image processing, and the method comprises the steps: placing a to-be-detected wood sample in a terahertz imaging device, collecting a multi-view reflection signal, obtaining a frequency domain signal through FFT transformation, and mapping a frequency spectrum into a two-dimensional image to form an initial view image set; performing quantum DNA coding on the pixel value of each image, performing mapping by adopting four bases to generate a DNA image matrix, rearranging pixel addresses by using a Hilbert curve traversal method, and outputting a disturbed image; converting the disturbance image into a one-dimensional time sequence signal, and establishing an AR model to obtain a preliminary enhanced image; according to the method, the separability and identifiability of the defect edge are effectively improved, and three-dimensional expression and highlight display of the geometric morphology of the defect are realized through three-channel pseudo-color mapping and three-dimensional voxel grid modeling.

The present invention relates to the field of quantum imaging technology, and more specifically, to a system and method for quantum imaging through scattering media based on light modulation and a genetic algorithm. The system and method include a generation and measurement unit, an optimization and shaping unit, and a verification and evaluation unit. The system modulates a spatial light modulator using a modulation signal to obtain initial modulated light, measures the initial modulated light using a detector, and obtains an initial image. The maximum and minimum values ​​of the intensity distribution of the initial image are obtained from a histogram of the initial image, and the contrast of the initial image is calculated based on the maximum and minimum values ​​of the intensity distribution of the initial image. An objective function is then defined based on the contrast value of the initial image. A control center introduces a genetic algorithm based on the objective function to optimize the initial modulation signal to find a modulation signal that maximizes the difference between bright and dark areas in the intensity distribution of the initial image, and calculates the peak signal-to-noise ratio of a final image generated corresponding to the modulation signal to evaluate the imaging quality.

The present invention discloses a quantum image encryption method based on a quantum long short-term memory network and a chaotic system, comprising the following steps: S1 uses a quantum long short-term memory network to improve a chaotic sequence generated by a hyperchaotic Lorenz system; S2 controls the three-level radial diffusion through the improved chaotic sequence to change the grayscale value of the quantum image; S3 controls the quantum Arnold transformation through the improved chaotic sequence to disrupt the position of the quantum image. The present invention combines a quantum long short-term memory network with a chaotic system for quantum image encryption for the first time, and by virtue of the characteristics of quantum mechanics itself, including entanglement and superposition, and the non-periodicity and unpredictability of chaotic sequences, not only the security of encryption is improved, but the combination of the two can better destroy the strong correlation between adjacent pixels, and at the same time, the key is concise and the decryption process is simple, which greatly reduces the technical content and time required for decryption, and effectively ensures the security of image information.

The invention provides a guide type quantum visual image recognition method and device. The method comprises the following steps: designing a guide normal form based on a visual high and low frequency complementary mechanism; and constructing an enhanced quantum classical hybrid model based on the guide normal form for quantum image recognition. The enhanced quantum classical hybrid model comprises an early visual cortex module for extracting low spatial frequency (LSF) information of an input image; the orbital frontal cortex module is used for generating initial prediction based on LSF information and positioning a potential HSF region based on an attention mechanism; the ventral visual pathway module is used for identifying an HSF region based on a high-frequency complexity index of two-dimensional discrete Fourier transform; and the fusiform module is combined with the orbital frontal cortex module and the ventral visual pathway module to obtain the HSF region, and high-spatial-frequency HSF information identification is carried out by utilizing a quantum reupload circuit. According to the invention, the efficiency and accuracy of image classification can be improved.

A method for imaging an object illuminated with natural light including arranging an optical filter in an optical path of at least a portion of the natural light that is reflected and / or refracted or scattered from the object; arranging an optical detector in an optical path of light at least one of reflected from and / or transmitted through the optical filter; detecting, using the detector, individual photons for a time period to provide a times series of individual photon events; segmenting the time series into a plurality of bins; determining a number of detected photons within each bin to provide a time series of photon counts per bin; replacing and / or reconfiguring the optical filter a plurality of times followed by detecting, segmenting and determining to obtain a plurality of times series of photon counts per bin; and forming an image of the object based on the plurality of times series.

The application discloses a kind of based on quantum network's image classification method and system, including obtaining the quantum image classification network and training data set of training completion;Initial coprocessing quantum classifier is constructed and coprocessing quantum classifier is trained;Quantum denoising self-encoder is constructed and Gaussian noise is added in training data set to obtain noisy training data set;Noisy training data set is input to current quantum denoising self-encoder and the gap is calculated;Image output by quantum denoising self-encoder is input into coprocessing quantum classifier and loss is calculated;The quantum denoising self-encoder constructed is trained using gap and loss to obtain trained quantum denoising self-encoder;The anti-noise quantum image classification network of trained quantum denoising self-encoder and the quantum image classification network of training completion is connected in series to obtain, and image classification is carried out.The application not only realizes the image classification based on quantum network, but also has high reliability, good accuracy and good stability.

This invention relates to the field of chaotic system theory and discloses a quantum image encryption algorithm based on chaotic systems and DNA dynamic coding. The algorithm includes a quantum image coding module, a chaotic sequence generation module, a DNA dynamic coding and operation module, and a central control module. The algorithm also integrates a key management unit. By using an enhanced quantum phase representation method to convert classical images into quantum images, and utilizing quantum gate operations controlled by chaotic sequences to achieve quantum scrambling of pixel positions and preliminary diffusion of pixel values, the system can efficiently perform preliminary confusion and perturbation of image information directly at the quantum level, laying a secure preprocessing foundation for subsequent encryption. By using a parallel multi-chaotic system to generate a dynamic key stream and introducing a dynamic perturbation mechanism based on image hash values, the generated key stream has stronger randomness and is dynamically related to the plaintext image content, enhancing its ability to resist security threats.