479 results about "Intermediate image" patented technology

The invention discloses a machine vision-based automatic identification and calculation method for pore change of a rock section under an SEM (scanning electron microscope), and the method comprises the steps: obtaining original image data of the rock section through a scanning electron microscope, transmitting the original image data to a machine vision SEM pore intelligent quantification cloud platform, and dividing the original image data into a plurality of image sub-regions which are not overlapped with each other; calling a special threshold inversion model to analyze the gray information of each sub-region, and determining a dual-phase pore segmentation threshold; carrying out edge extraction on the sub-regions after threshold processing by adopting a pore edge gradient enhancement algorithm; performing topological structure analysis on the intermediate image data by using a biphase pore topological inversion model, constructing and optimizing a pore space topological network, and eliminating false pore structure data; and according to the optimized pore space topology network, integrating calculation results of all the sub-regions to obtain a pore change identification calculation result of the whole rock section. The method improves the pore identification precision and processing efficiency, and adapts to different types of rock samples.

A method for digitizing image-based data includes receiving an image file including one or more target objects, generating an intermediate image by removing noise from the image file using a denoising machine learning model, identifying the one or more target objects included in the intermediate image using an object segmentation machine learning model, discretizing the one or more target objects that were identified using the trained object segmentation machine learning model, and storing the one or more target objects that were discretized in a data file, visualizing the one or more target objects, or both.

The invention discloses a lightweight high-speed photographing system and method based on an event camera, and the system comprises a hybrid imaging module which is used for synchronously collecting the image data and event data of a scene, and comprises a visible light camera and an event camera; the hardware synchronization module is electrically connected with the visible light camera and the event camera, and is used for receiving a frame synchronization signal of the visible light camera and sending a trigger signal to the event camera, so that the event camera inserts a time stamp corresponding to a visible light image frame exposure moment in an event stream; the data processing and fusion unit is in communication connection with the hybrid imaging module and is used for receiving the image data and the event data and executing the following steps: performing time alignment on an event stream and a visible light image frame stream based on a time stamp; operating a high-frequency frame insertion reconstruction algorithm, and reconstructing a multi-frame intermediate image by using event stream data between two frames; synthesizing the original visible light image frame and the reconstructed intermediate image into a high-frame-rate video stream; and the power supply and interface module is used for supplying power to the system and outputting a high-frame-rate video stream.

The invention relates to a cross-modal retrieval technology, in particular to a cross-modal image-text pedestrian retrieval method based on a generative model, which comprises the following steps: acquiring text description information and a corresponding original pedestrian image; calling a diffusion generation model to generate an intermediate image based on the text description; original image features and text features are extracted through an image encoder and a text encoder respectively, and semantic-fused text feature representation is constructed; calculating the similarity between the image feature representation and the text feature representation to obtain an image-text matching score; introducing and generating an intermediate image as a semantic bridge, and realizing multi-modal fusion among the image, the text and the intermediate image through a cross attention mechanism to obtain fused image and text features; and using the fusion features to train a recognition model, and finally outputting a pedestrian image retrieval result corresponding to the text description. According to the method, the image-text alignment precision can be improved, the robustness of a scene with incomplete text description is enhanced, and the recognition accuracy in a cross-modal retrieval task is improved.

Disclosed are systems, apparatuses, processes, and computer-readable media for processing one or more images. For example, a method includes obtaining an inpainted image based on providing a first image to an ML model; combining the first image and a first auxiliary image of the first image into an intermediate image; obtaining an inpainted intermediate image based on providing the intermediate image to the ML model; and generating a second auxiliary image from the inpainted image and the inpainted intermediate image.

A method, apparatus, non-transitory computer readable medium, and system for generating images includes obtaining an image generation prompt and a reference prompt. The image generation prompt includes a first element and a second element and the reference prompt includes the second element. Embodiments then generate, using an image generation model, an intermediate image based on the reference prompt. Subsequently, embodiments generate, using the image generation model, a synthetic image including the first element and the second element based on the intermediate image and the image generation prompt.

Provided in the present disclosure are an image generation method and apparatus, an image processing model training method and apparatus, an image processing method and apparatus, and an electronic device and a storage medium, which can be applied to the fields of computer technologies, deep-learning technologies and image processing technologies. The image generation method comprises: on the basis of an initial noise image and an image category, determining a first noise image; on the basis of the initial noise image and the first noise image, determining a first intermediate image; and on the basis of the first intermediate image, generating a first target image that belongs to the image category.

The invention relates to the technical field of semantic segmentation, in particular to a night semantic segmentation method based on low illumination enhancement and edge optimization, and the method comprises the steps: inputting an image into a low-light enhancement repair network based on the Retinex theory, local contrast enhancement and adaptive feature fusion, obtaining a denoised and enhanced intermediate image, and carrying out the edge optimization of the intermediate image; inputting the intermediate image into a semantic segmentation network to obtain a category distribution diagram of each pixel; inputting a discriminator embedded with a channel attention module according to the category distribution diagram of each pixel, and optimizing a generator composed of a low light enhancement repair network and a semantic segmentation network through a multi-task joint optimization loss function; and inputting a night image to be detected and segmented into the optimized generator, and outputting a segmentation result. By adopting the method, the low-light enhancement repair network is combined with a local contrast enhancement and channel feature fusion mechanism, so that the overall brightness of the image is improved, the details and edge structures of the image are reserved, and the perception capability and robustness of the model are improved.

The invention relates to the technical field of image processing, and provides a construction site image processing method, device and equipment, and a medium, which can identify a non-target object in a target construction site image, generate a mask in the target construction site image according to an identification result, roughly position the non-target object, and generate a mask in the target construction site image according to the identification result. Accurate target segmentation is carried out according to positioning, so that the processing efficiency and precision can be effectively balanced; the target construction site image is erased according to the mask to obtain a first intermediate image with a blank area, and content completion is performed on the blank area based on an environment perception algorithm to obtain a second intermediate image, so that the problem of feature matching failure caused by dynamic interferents can be solved, and meanwhile, the structural integrity of a building main body is ensured; and detail reduction processing is performed on the second intermediate image based on the spatial semantic information of the building information model, so that the influence of illumination variation and shielding interference can be reduced, and a high-quality image which is more suitable for executing a construction site monitoring task is generated.

The invention relates to the technical field of agricultural unmanned aerial vehicle data processing, in particular to an agricultural unmanned aerial vehicle pod sensor data processing method and system which are used for correcting image data abnormity caused by spraying operation. Synchronously acquiring image data acquired by an optical sensor and vibration data acquired by a vibration sensor and generated by the spraying system during working; determining a characteristic vibration frequency according to the vibration data, and performing frequency domain filtering processing on the image data based on the characteristic vibration frequency to generate intermediate image data of which the vibration blur is eliminated; by synchronously acquiring the image and the vibration data, correcting the vibration blur by using the vibration data, identifying and confirming the lens liquid drop by using the spectral characteristics and the position fixity, and generating the mask layer to shield the liquid drop area, the problems of missed judgment and misjudgment of the liquid drop as a disease caused by the vibration blur are solved.

An optical system is configured to guide light from a light source to a first target and a second target, and to guide first reflected light from the first target and second reflected light from the second target to an image sensor. The optical system includes a first optical element having a conical surface. An intermediate image is formed between the first optical element and each of the first target and the second target. The first reflected light and the second reflected light are guided to an imaging plane of the image sensor such that at least part of the first reflected light and part of the second reflected light overlap each other on the imaging plane.

An optical assembly (17) has a primary optical rod (28) for guiding illumination light (4) along an illumination light beam path from a light source to a target field. An optical follower rod (29) of the optical assembly (17) is arranged in the illumination light beam path between the primary rod (28) and the target field. An intermediate image-generating optic (30) is arranged between the primary rod (28) and the follower rod (29). This generates an intermediate image between the primary rod (28) and the follower rod (29) along exactly one imaging dimension (y) perpendicular to the illumination light beam path. The result is an optical assembly in which the illumination light, after passing through the optical assembly, has a defined polarization state. The optical assembly can be part of an illumination optic and can, in particular, be part of an optical system of a projection exposure system containing such an illumination optic.

The invention discloses an image reconstruction method and system, a terminal and a storage medium, and the method comprises the steps: reconstructing a limited angle image through a reconstruction algorithm, and obtaining an intermediate image; using a registration algorithm to align prior information to the intermediate image to obtain registration prior information; and processing the limited angle image based on the registration prior information to obtain a reconstructed limited angle image. According to the method, the prior information with similar structures is introduced, and information fusion is realized by means of registration, so that the problems of artifacts and fuzziness caused by incomplete data in limited angle imaging are effectively solved, the quality and stability of image reconstruction are improved, and the method has good clinical applicability and engineering application value.

The present disclosure performs image in-painting with controlled text generations to overcome the challenges persisting in traditional diffusion-based methods, especially when it comes to generating textual content within the image with complex font attributes. In the present disclosure, initially, an input image and a textual prompt and a plurality of control parameters are given as input to the present disclosure. Further, character mask and conditional mask are extracted based on the inputs. Finally accurate customized textual images are generated based on the character mask and the conditional mask using a textual image generating diffusion model. The textual image generating diffusion model generates an intermediate image based on the input image and the random gaussian noise. This intermediate image is iteratively refined to generate a latent vector image, and the accurate customized textual image is generated from the latent vector image using a trained customized character map-guided consistency model.

System and method for Generative Artificial Intelligence based image generation are disclosed. In an aspect, a user input is received requesting an image of a predetermined object to be generated. An enhanced prompt is then generated from the user input, the enhanced prompt includes one or more of a reference image of the predetermined object and a textual portion describing technical details for generating the image. Further, the enhanced prompt is input to an image generation model that preserves portions of the reference image including the predetermined object unchanged via masking the portions of the reference image, generates a depth map of the reference image, and generates an intermediate image by merging the reference image with the masked portions of the predetermined object and the depth map. Also, an enhanced version of the intermediate image is output as the image generated in response to the user input.

A computer-implemented method for determining an estimation of a two-dimensional scattered radiation distribution in a two-dimensional X-ray image that is based on an imaging procedure performed by an X-ray detector is provided. The method includes receiving the X-ray image, applying an estimation algorithm to the X-ray image or to a two-dimensional intermediate image determined from the X-ray image. The estimation algorithm determines a respective two-dimensional partial scattered radiation image for a plurality of physical scatter processes such that image values of pixels of the respective partial scattered radiation image in each case describe an estimated value for a respective scattered radiation dose that was applied to a respective detector region of the X-ray detector assigned to the respective pixel during acquisition of the X-ray image by the respective physical scatter process. The estimation of the scattered radiation distribution is determined based on the plurality of partial scattered radiation images.

The invention relates to the technical field of image processing, in particular to a double-stage image restoration method for composite degradation, which comprises the following steps of: S1, inputting a degraded image into a restoration module to generate an intermediate image without degradation; the recovery module comprises an encoder and a decoder, the encoder adopts a Transform block to process cross-scale features in a spatial domain, the decoder adopts a WaveTrans block to recover image resolution, and composite degradation is removed in a frequency domain; s2, inputting the intermediate image into a generation module, and generating a clear image after detail reconstruction; the generation module introduces a signal refining module and a frequency modulator for improving the image quality. According to the method, a two-stage model is provided, so that the restoration effect of the composite degraded image is effectively improved.

A method for processing image data may include: obtaining a raw input image that is captured under an input illumination; obtaining a target illumination from a user input; obtaining an intermediate image having colors captured under a reference illumination, from the raw input image, based on a first color transform that maps the input illumination to the reference illumination in an illumination dataset of raw sensor images that are captured under a plurality of different illuminations; and obtaining an output image having colors captured under the target illumination, from the intermediate image, based on a second color transform that maps the reference illumination in the illumination dataset to the target illumination.

The invention relates to the technical field of intelligent models, and discloses an image generation method and device, computer equipment, a storage medium and a program product. Similar preset prompt words, a potential classification list of a to-be-generated image and confusion category pairs are determined on the basis of original prompt words, so that the confusion category pairs are utilized to carry out classification correction; misjudgment of the subject category of the to-be-generated image is avoided, and the accuracy of the subject category is improved. And if the theme category is a character theme, optimizing the original cue word through the scene type of the to-be-generated image to obtain a target cue word, so that the image generation model performs image generation by using the target cue word with rich details and the scene type. When iteration of the image generation model is not finished, face restoration is carried out on the intermediate image generated by the image generation model, so that generation time prolonging caused by image restoration after iteration is finished is avoided, image generation efficiency is improved, a face collapse phenomenon is avoided, and image generation quality is improved.

An imaging system having multiple imaging devices arranged in succession in the direction of an optical axis, including a first imaging device for generating a real intermediate image of an object on an intermediate image plane, a second imaging device for generating a virtual mirror image of the real intermediate image, the mirror image being laterally offset to the real intermediate image on the intermediate plane, and a third imaging device for imaging the real intermediate image and the virtual mirror image together as a real image on an image receiver surface to be arranged at an axial distance to the intermediate image plane. The imaging system has an optical filtering device for filtering the imaging of the real intermediate image and / or at least one of the virtual mirror images separately from each other. The imaging system includes the image receiver surface and a device for processing a real image captured by the image receiver surface. The processing device uses the image to determine positions in the direction of the optical axis of object region points, which are imaged by at least individual pixels of the pixels of the image.

The invention discloses an image defogging method and system based on a physical guide diffusion model, and relates to the technical field of image processing. Comprising the following steps: inputting a to-be-processed fog image into a trained physical perception defogging model to obtain a pseudo clear image (namely a preliminarily estimated fog-free image) and a transmissivity image (representing the attenuation degree of a medium to scene light); inputting the to-be-processed fog image into a pre-trained physical guide diffusion model, and gradually adding Gaussian noise to the clear image through a Markov chain to generate a noise image; the pseudo clear image and the transmissivity image serve as input through condition guidance, and feature splicing is adopted to be injected into a diffusion model so as to guide the denoising direction; then capturing the characteristics of noise distribution by using a diffusion model, predicting and removing noise components in the current time step, and obtaining an intermediate image; and taking the intermediate image corresponding to the final time step as a defogged clear image. According to the method, the accuracy of the denoising direction is emphasized, and the definition and quality of the defogged image can be improved.

The invention discloses an optical cement surface defect detection method and system based on visual inspection. The method comprises the steps that an original image set is acquired and preprocessed to obtain an intermediate image sequence; performing dynamic noise estimation on the intermediate image sequence, and selecting a high-frequency noise region in the intermediate image sequence for optimization to obtain a stable image sequence; defect detection is carried out on the stable image sequence, edge texture enhancement processing is carried out after preliminary defect area distribution is obtained, coordinates are mapped, and defect positioning coordinates are obtained; performing real defect judgment on the image according to the defect positioning coordinates to obtain a defect aggregation degree, dividing a high-density aggregation region, extracting the defect size of the high-density aggregation region, and generating a defect distribution mapping graph in combination with the defect aggregation degree; and carrying out image superposition according to the mapping graph and the original image set, and carrying out risk assessment on the high-density defect area according to the superposed image to obtain a final defect detection report. According to the method, accurate detection and analysis can be ensured when tiny defects are processed.

The invention belongs to the technical field of computer vision and digital media, and discloses a dome-screen film production method and system based on a high-altitude aerial image. Projecting the multi-view aerial video sequence to a unified spherical coordinate system, and constructing a panoramic space with an overlapping region; performing non-rigid geometric deformation processing on the overlapping region of the panoramic space to generate an intermediate image with aligned pixels; calculating the fusion cost of each pixel point in the overlapping region in the intermediate image, and performing path search based on the fusion cost of each pixel point to generate a dynamic suture line; generating an image mask based on the dynamic suture line, performing multi-scale frequency domain adaptive fusion on the intermediate image by using the image mask to generate a fused panoramic image, and remapping the fused panoramic image into a projection format adaptive to dome screen playing to output; and the real reducibility and the manufacturing quality of the dome film are greatly improved.

An eyewear display device implements a curved lightguide to form an intermediate image between an incoupler and an outcoupler. The curved lightguide produces an approximately 20-degree diagonal field of view (FOV) full-color display having approximately 10% red, blue, green efficiency with uniform color and luminance for a micro-display at a temple of an eyewear display device. The curved lightguide incorporates freeform mirror incouplers and / or outcouplers and color-corrected relay optics. Using an intermediate image stage in the optical pathway allows for use of a compact incoupler that does not exceed a thickness of the curved lightguide.

The invention provides a cross target center positioning method and device. The method comprises the following steps: intercepting a coarse positioning image according to an initial grayscale image and a corresponding candidate area; at least performing gradient calculation on the coarse positioning image to obtain a first intermediate image; determining a target row matrix and a target column matrix from the first intermediate image, taking pixels at corresponding positions in the coarse positioning image as mark points, performing region division on the coarse positioning image to obtain a plurality of candidate rectangular blocks, the target row / column matrix being a plurality of row / column matrixes with the maximum pixel value weighted sum, and the target column matrix being a plurality of candidate rectangular blocks with the maximum pixel value weighted sum; each candidate rectangular block comprises a main body part formed by non-mark points; calculating a center score of each candidate rectangular block according to a preset rule; and taking the center of the candidate rectangular block with the highest center score greater than the score threshold as the center of the cross target corresponding to the initial grayscale image. According to the method and the device, environmental interference can be effectively resisted, and the center of the cross target can be quickly and accurately positioned in visible light, infrared and low-light scenes.

The invention discloses a large-view-field space detection optical lens. The large-view-field space detection optical lens comprises a front lens group, a diaphragm, a rear lens group and an image surface which are sequentially arranged from an object side surface to an image side surface, the front lens group filters incident light waves and forms an intermediate image; the diaphragm controls the luminous flux by adjusting the relative aperture of the diaphragm; the rear lens group amplifies the intermediate image, corrects aberration and performs optical imaging through an image surface; the front lens group comprises a first optical filter, a first negative meniscus lens, a first biconvex lens and a second biconvex lens which are sequentially arranged from a position far away from the diaphragm to a position close to the diaphragm; and the rear lens group comprises a first biconcave lens, a third biconvex lens, a fourth biconvex lens, a first positive meniscus lens, a second negative meniscus lens, a second positive meniscus lens, a third negative meniscus lens and a second optical filter which are sequentially arranged from the diaphragm to the image plane. The optical lens provided by the invention has the characteristics of circular light spot, large view field, low chromatic aberration, low distortion, high resolution and small form deviation of light spots in each view field.

A Raman spectroscopy apparatus comprises an imaging optical system that transmits light from an object to a spectrograph along an optical path. A scanning device intersects, and is movable with respect to, the optical path. Light is directed onto the scanning device to illuminate the object at a plurality of illumination points. The imaging optical system transmits Raman scattered light emitted from the object at the illumination points to an intermediate image plane, the scanning device being located at the intermediate image plane, and transmits the Raman scattered light from the intermediate image plane to the spectrograph. In comparison with conventional confocal Raman spectroscopy, the apparatus can perform Raman analysis of a sample more quickly, and in comparison with conventional line scan Raman spectroscopy the apparatus can perform Raman analysis more accurately.

This invention provides a method for detecting adhesive buildup on the surface of a running track, comprising: acquiring an HSV image corresponding to the running track to be tested; performing a first image processing on the HSV image to obtain a first intermediate image identifying a feature region; the feature region consisting of undifferentiated adhesive buildup areas and interference areas; performing a second image processing on the HSV image to obtain a second intermediate image identifying interference areas; and determining the target information of the adhesive buildup on the surface of the running track to be tested based on the first and second intermediate images. A running track surface adhesive buildup detection device, a computer device, and a storage medium are also provided. Using the HSV color model, and through relevant image processing on the HSV image, the target information of the adhesive buildup on the surface of the running track to be tested is finally determined; compared with manual visual inspection, this method can greatly improve detection efficiency, reduce labor costs, and accurately determine the target information such as the area of ​​the adhesive buildup on the surface.

A microscope for imaging a sample by a transmitted light contrasting method includes an objective lens holder configured to place an objective lens of a number of objective lenses onto an optical axis of the microscope. The microscope further includes a lens system for forming an intermediate image of an exit pupil of any one of the number of objective lenses placed onto the optical axis. The intermediate image is formed at a respective conjugated plane conjugate to the exit pupil. The microscope further includes a control device configured for automatically positioning a modulation element onto the optical axis at a positon related to the respective conjugated plane.