111 results about "Global illumination" patented technology

The invention discloses a complex material-oriented global full-frequency illumination neural rendering method and system, and belongs to the technical field of computer graphics, and the method comprises the steps: querying and extracting a primary frequency feature and a secondary frequency feature in a neural feature field according to the primary geometric buffer and the reflection geometric buffer of a rendering pixel; performing weighted combination on the primary frequency features and the secondary frequency features through a double-frequency fusion module to form full-frequency fusion features; inputting the full-frequency fusion feature and the initial geometric buffer into a decoder to obtain a pixel radiation brightness value; and optimizing the network by adopting a double-stage training strategy of low-frequency data and multi-frequency data, and then using the optimized network for neural drawing of global full-frequency illumination. The method can improve the accuracy and stability of global illumination simulation in a complex dynamic scene, and is suitable for modeling a multi-frequency global illumination effect in a dynamic three-dimensional scene.

The invention relates to an underwater image processing technology in the field of underwater autonomous perception, in particular to an underwater low-quality image enhancement method based on a Laplacian pyramid and contrast learning. Comprising the following steps: S1, image input and multi-scale decomposition: decomposing an input image into a low-frequency residual layer and a plurality of high-frequency detail layers through Laplacian pyramid decomposition; s2, inputting the low-frequency residual error layer into a global illumination and color correction sub-module to obtain an enhanced low-frequency residual error layer; s3, inputting the enhanced low-frequency residual error layer and the multi-scale high-frequency detail layer into a frequency domain enhancement feature module to obtain multi-scale enhanced high-frequency detail layer output; s4, performing progressive reconstruction on the enhanced low-frequency layer output and the high-frequency enhancement layer output of each scale according to the inverse process of the Laplacian pyramid; and S5, outputting a result and applying. The method can be used for sharpening optical image data in the operation task of the autonomous underwater vehicle, and the image quality is improved.

The invention discloses an endoscope image processing method and system for improving image quality, and relates to the technical field of image processing.The method comprises the steps that a highlight reflection area of an endoscope image is extracted by setting a detection and extraction mechanism of the highlight reflection area; the method comprises the following steps: dividing an image of which a highlight reflection region is extracted into a base layer and a detail layer, performing global illumination adjustment on the base layer, performing detail enhancement on the detail layer, and fusing the enhanced base layer and detail layer to obtain a pre-enhanced image; if the pre-enhanced image extracts an over-high-brightness area, repairing a high-brightness reflection area and outputting the high-brightness reflection area; according to the method, global enhancement of the endoscope image is realized through highlight reflection area detection, image hierarchical processing and highlight reflection area repair, and the visibility and availability of the endoscope image are improved.

The invention discloses an efficient three-dimensional scene anti-rendering method and system based on a multi-view image and a storage medium, and the method comprises the steps: employing a neural symbol distance function network as a geometric model to represent a scene geometric structure of the multi-view image, decomposing a neural radiation field into a diffuse reflection field and a specular reflection field, in combination with the self-shielding probability of the mirror reflection field, the diffuse reflection field, the mirror reflection field and the self-shielding probability of the mirror reflection field, calculating color information of the spatial points and optimizing the geometric model; a material network is adopted to represent albedo and roughness and obtain material information, color information cached in a neural radiation field, an illumination visibility function and direct illumination are introduced, global illumination of each light ray is calculated, importance sampling and illumination Monte Carlo integral are combined to obtain a rendering result, and the material network and a direct illumination network are optimized; and on the basis of the geometric structure, the material information and the illumination information obtained by the decoupled geometric model, the material network and the direct illumination network, a high-quality image is generated by adopting rendering pipeline calculation.

The invention relates to the field of image correction, and provides an image correction method, device and system and a storage medium, and the method comprises the steps: synchronously collecting a color image and three-dimensional point cloud data of a target object through an RGB-D sensor, constructing an elastic mesh model (including a rigidity attribute), and achieving the high-precision surface expansion based on finite element analysis. Generating a geometric correction image; in combination with a multispectral shadow separation and generative adversarial network (GAN) restoration technology, shielding shadows are eliminated, and textures with consistent illumination are generated; and finally, optimizing global illumination uniformity through dynamic compensation perceived by ambient light. Through the technical scheme, the error of expansion correction of a non-planar object is reduced, the real content and the shadow area are efficiently distinguished, the dynamic ambient light change is adapted in real time, and the complex texture generation capability is improved.

The invention provides an illumination rendering method for a game scene and electronic equipment, and belongs to the technical field of global illumination. According to the method, the voxelization processing area is determined based on the observation point, only voxelization processing needs to be carried out on the scene in the limited range around the observation point, the calculation complexity can be greatly reduced, and memory resource occupation is reduced; tasks are distributed through a main thread, and a plurality of background threads execute voxelization processing in parallel, so that the utilization rate of a GPU can be improved, and blockage of the main thread can be avoided; by determining the processing priority of the voxel blocks, the voxel blocks which greatly influence the picture effect can be processed preferentially, real-time updating of the illumination effect of the central area of the visual field of a player is ensured, and delay or distortion of the key area of the picture is avoided.

The invention relates to a space-frequency domain collaborative low-light deblurring method based on Fourier transform and Mama architecture, and belongs to the technical field of image processing. According to the method, an image is decomposed through Fourier transform, and effective separation of low light degradation and fuzzy degradation is achieved at a frequency domain source according to the physical characteristics of amplitude spectrum dominant illumination and a phase spectrum dominant structure. In order to solve the problem of accurate reconstruction of frequency domain information in a spatial domain, a space-frequency domain double-branch collaborative architecture is constructed, global illumination recovery and local detail enhancement are respectively focused through low-frequency and high-frequency processing branches which are explicitly distinguished in the spatial domain, and frequency domain decoupling advantages and spatial domain sensing capability are adaptively bridged by combining a dynamic feature fusion mechanism. Meanwhile, in order to process different degradation types in the recovery process, a task-oriented decoupling optimization strategy is designed, the strategy activates amplitude adjustment and low-frequency optimization in the encoding stage to deal with low-light enhancement preferentially, and activates phase reconstruction and high-frequency enhancement in the decoding stage to process blurring removal in a targeted mode.

The invention discloses an infrared bidirectional thermal effect simulation method based on radiation and GPU acceleration, and belongs to the field of thermal radiation simulation and parallel computing. Dispersing the complex geometry into patch units, constructing an inter-patch radiation energy balance equation based on a radiance theory, and iteratively solving the final temperature of the patches through a radiance method; a three-level parallel strategy of a task level, a data level and an instruction level is designed, data intensive tasks such as shape factor calculation and radiance iteration are migrated to a GPU to be executed, data storage is optimized in combination with a structure array (SoA) layout and a sparse matrix compression technology, and efficient data sharing of a CPU end and a GPU end is achieved through a CUDA zero copy technology. According to the method, the dependence of a traditional method on regular grids is broken through, the calculation efficiency and precision of million-level surface patch heat radiation transmission in a complex scene are remarkably improved, and an efficient tool is provided for heat radiation indirect transmission calculation and a global illumination model in the field of three-dimensional scene infrared simulation.

The embodiment of the invention provides a global illumination rendering method, electronic equipment and a storage medium, belongs to the technical field of computer graphic processing, is applied to illumination rendering of a three-dimensional modeling scene, and comprises the following steps: obtaining an original picture without adding a global illumination effect, a corresponding camera viewpoint and a corresponding camera viewpoint; acquiring originally corresponding illumination radiation data based on a camera viewpoint, and determining the originally corresponding illumination radiation data as irradiance cache data; in response to the change of the camera viewpoint, performing ray tracing processing based on the changed camera viewpoint to obtain changed illumination radiation data; performing fusion processing on the irradiance cache data and the changed illumination radiation data to obtain target illumination radiation data; and performing global illumination generation based on the target illumination radiation data to add a global illumination effect to the original picture to obtain a target picture. According to the embodiment of the invention, the calculation complexity of indirect illumination can be reduced, and a global illumination effect is obtained.

The invention discloses a land environment shadow region optical feature recovery method and system, and the method comprises the steps: synchronously collecting a visible light image, a near infrared spectrum image and three-dimensional point cloud data of a target land region through a multi-mode sensor, and generating multi-source fusion data with a space-time alignment attribute; based on the multi-source fusion data, constructing an illumination transmission physical model of the scene, and separating a direct illumination attenuation component and an indirect illumination diffuse reflection component of a shadow region; performing compensation reconstruction on the direct illumination attenuation component by using a generative adversarial network, and generating an initial recovery image after shadow elimination; and outputting a final recovered image with global illumination consistency and local detail authenticity by adopting a cross-scale attention fusion mechanism. By using the embodiment of the invention, the real spectral attribute and rich spatial texture details of the ground feature can be maintained, and the visual consistency of the image and the reliability of subsequent quantitative application are improved.

The invention discloses a low illumination enhancement method based on event and image bidirectional collaborative guidance, and belongs to the technical field of computer vision. The method comprises an event feature extraction branch and an image-event fusion branch which are respectively provided with an image-guided event enhancement module and a Mama-based image-event fusion module; the two modules realize cross-modal interaction through bidirectional cooperative guidance. The image-guided event enhancement module suppresses event noise and compensates for context loss by using semantic context information of an image. The Mama-based image-event fusion module adjusts the global illumination and contrast of the image by using the global representation capability of Mama and the characteristics of linear space-time complexity, and fuses event data to the image in combination with a signal-to-noise ratio map to supplement structural information. According to the method, enhancement and fusion of the image and event information are realized through a bidirectional collaborative guidance mechanism, and the enhancement problems of image structure deficiency and illumination contrast degradation in a low-illumination scene are solved.

The invention discloses a medical image intelligent diagnosis and three-dimensional visualization interaction method and system based on artificial intelligence and Unreal Engine. The system is composed of a data acquisition module, an artificial intelligence analysis module, a three-dimensional reconstruction module, a rendering interaction module and a report generation module. The method comprises the following steps: firstly, carrying out voxel normalization on a DICOM / NIfTI image; the improved 3D U-Net is combined with CBAM attention and WGAN-GP training, and a focus initial density field is output; an AI enhanced implicit voxel reconstruction (AEIVR) algorithm is proposed, an enhanced density field is generated by using position coding + MLP, and grid extraction is completed by using improved Marking Cubes of a dynamic threshold; high-fidelity real-time rendering is realized in combination with a Nand micro polygon and Lumen global illumination in Unreal Engine, and VR / AR interaction and virtual surgery (real-time updating of resection mask driving) are supported. According to the method, the problems of large artifacts and insufficient interactivity and real-time performance of existing two-dimensional output and three-dimensional reconstruction are solved, and the end-to-end segmentation-reconstruction-rendering-interaction-reporting process is realized. On typical CT / MRI data, the segmentation Dice is about 0.90-0.94, the reconstruction voxel resolution is 0.1-0.5 mm, the artifacts are reduced by about 20%-30%, the PSNR is improved by about 3-7 dB, and the rendering interaction delay lt is achieved; the system is suitable for scenes such as lung CT, brain MRI, orthopaedic X-ray and cardiac ultrasound, and can be expanded to preoperative planning, remote consultation and teaching.

The invention relates to the technical field of image processing, and discloses a tea maturity detection method and system, and the method comprises the steps: obtaining an original image of tea in a natural illumination imaging environment; generating a global illumination difference chart representing an ambient illumination state, and performing illumination compensation on the to-be-detected area of the tea in the original image to obtain a compensated image of the tea; performing gray scale range adjustment on the compensated image of the tea leaves to obtain an enhanced spectral image of the tea leaves; integrating the color and spectral characteristics of the specific spectral reflection characteristics of the tea leaves with different maturity degrees in the enhanced spectral image and the three-dimensional morphological characteristics reflecting the spreading degree and thickness of the tea leaves into the fusion image characteristics of the tea leaves; mapping the color spectrum emission characteristics and texture characteristics of the tea leaves in the enhanced spectrum image to a maturity discrimination knowledge base of the tea leaves to obtain a preliminary maturity result; performing confidence coefficient weighting on the preliminary maturity result to obtain a target maturity; according to the invention, the tea maturity detection efficiency can be improved.

The invention provides an image enhancement method based on double-domain illumination prior and electronic equipment, and relates to the field of image processing. The method comprises the steps of obtaining a to-be-processed illumination image; according to local illumination distribution characteristics of the to-be-processed illumination image, multi-scale enhancement is carried out on the to-be-processed illumination image after global illumination enhancement, a first illumination image after spatial domain enhancement is obtained, and the local illumination distribution characteristics comprise a brightness mean value and a brightness standard deviation; amplitude information of the to-be-processed illumination image in the frequency domain is enhanced, and a second illumination image enhanced in the frequency domain is obtained; and fusing the to-be-processed illumination image, the first illumination image and the second illumination image to obtain an enhanced target illumination image.

Disclosed approaches provide for interactions of secondary rays of light transport paths in a virtual environment to share lighting contributions when determining lighting conditions for a light transport path. Interactions may be shared based on similarities in characteristics (e.g., hit locations), which may define a region in which interactions may share lighting condition data. The region may correspond to a texel of a texture map and lighting contribution data for interactions may be accumulated to the texel spatially and / or temporally, then used to compute composite lighting contribution data that estimates radiance at an interaction. Approaches are also provided for reprojecting lighting contributions of interactions to pixels to share lighting contribution data from secondary bounces of light transport paths while avoiding potential over blurring.

The invention relates to a method, a device and equipment for synchronously adjusting global illumination brightness of a train and a medium. The method comprises the following steps: acquiring a plurality of illumination data of a first train and a tail train of the train; performing data verification on the illumination data to remove corresponding abnormal data, and calculating the illumination data after the abnormal data is removed through dynamic weighting to obtain a current average illumination value; based on the current average illumination value, obtaining an illumination change trend in a preset time period through a preset illumination prediction model; generating an illumination adjustment instruction according to the illumination change trend, and synchronously issuing the illumination adjustment instruction to each compartment through a ring topology network; and calling a local dynamic gradient dimming algorithm to generate dimming control parameters based on the illumination adjustment instruction, and further controlling the illumination equipment to execute brightness adjustment operation. The method has the effect of reducing the brightness difference of the train carriages.

The invention discloses a global neural drawing method and system oriented to hybrid representation optimization, and belongs to the technical field of computer graphics, and the method comprises the steps: dividing a screen into a plurality of tiles, and obtaining a first workload index on each tile in a first drawing stage and a second workload index on each tile in a second drawing stage; generating a cross-tile and cross-stage unified scheduling queue based on the first workload index and the second workload index, and executing the drawing tasks on different tiles in parallel according to the unified scheduling queue; and triggering a subsequent feature fusion and neural global illumination drawing stage when the inter-stage dependency condition is met so as to generate an output image with a global illumination effect. According to the method, the end-to-end frame rate oriented to the modern AI accelerator / AI-GPU can be remarkably improved and the tail delay can be reduced on the premise of ensuring the visual quality and the time sequence stability, and the method is suitable for application scenes such as real-time global illumination, large-scale complex scene drawing and interactive neural rendering.

The invention provides an unmanned aerial vehicle target detection method and device based on infrared and visible light image fusion, and the method comprises the steps: collecting images of two modes of a same scene at the same time through a sensor carried on an unmanned aerial vehicle, and extracting global illumination information from a visible light image to generate an illumination weight, calculating weighting coefficients of the two modes according to the illumination weight; weighting the visible light feature map and the infrared feature map by using corresponding weighting coefficients to obtain weighted features; determining a frequency domain difference between the weighted features of the two modes, and enhancing the weighted features according to the frequency domain difference to obtain enhanced features; splicing the enhanced features of the two modes, respectively inputting a global branch and a local branch, obtaining a global offset field and a local offset field, superposing the global offset field and the local offset field to obtain a final offset field, and aligning the implicit positions of the infrared enhanced features by using the final offset field; and splicing the aligned enhanced features of the two modalities, and inputting the spliced enhanced features into a target detection head to obtain a target detection result. According to the invention, the target detection precision and robustness are improved.

The invention provides a global illumination rendering method and device, electronic equipment and a storage medium. The method comprises the steps that scene data are acquired, and the scene data comprise data needed by baking of an illumination probe and an auxiliary point preset in a scene; baking the scene according to the scene data to obtain a baking result; wherein the baking result comprises brightness baking results of the illumination probe and the auxiliary point, and spherical harmonic coefficient data of the illumination probe; according to the brightness baking results of the illumination probe and the auxiliary point, predicting internal and external information of the illumination probe relative to the target light source, and obtaining target internal and external information of the illumination probe; and when the scene is rendered, performing global illumination calculation of the object according to the target internal and external information and the spherical harmonic coefficient data of the illumination probe. The problem of internal and external light leakage of the illumination probe can be automatically solved, and meanwhile, the storage data volume, the operation overhead and the labor cost are balanced.

The invention discloses a 3D digital human mixed shadow generation method and system, a medium and equipment, and the method comprises the following steps: S1, main shadow generation: carrying out the real-time light tracing of a main light source, and generating a main shadow; s2, secondary shadow generation: generating a secondary shadow for the dynamic scene by using cascade shadow mapping; s3, soft shadow and penumbra processing: generating a soft shadow by using percentage asymptotic filtering or variance shadow mapping; s4, global illumination shadow: calculating the influence of indirect illumination on the main shadow, the secondary shadow and the soft shadow by using a real-time global illumination technology, and generating a global illumination shadow; s5, dynamic shielding processing: detecting the shielding relationship between the digital person and the environment in real time, and adjusting the generation algorithms of the main shadow, the secondary shadow and the soft shadow; s6, model optimization: using a deep learning model to carry out noise reduction or resolution improvement on the shadow; and S7, shadow synthesis: synthesizing the main shadow, the secondary shadow, the soft shadow and the global illumination shadow. The method has the advantages of improving the shadow quality and ensuring the real-time interaction of the shadow.

The invention discloses a multi-modal image processing method based on frequency perception and interactive fusion. The problem of image fusion under a low-light condition can be solved in a decoupling type double-branch parallel processing mode. The method comprises the following steps: importing a data set and performing characteristic decomposition, receiving visible light and infrared images, and decoupling each modal image into low-rank and sparse characteristics; carrying out interactive content fusion, carrying out cross-modal interaction on high and low frequency features through bilateral information exchange, carrying out enhancement, and reconstructing an intermediate fusion image; performing parallel global illumination estimation, inputting the visible light image into an illumination estimation network based on frequency domain processing, and generating an ideal illumination image; and performing physical illumination reconstruction and output, and performing brightness improvement on the intermediate fusion image to obtain a fusion image. According to the method, specialized processing of frequency perception and a cross-modal deep interaction mechanism are combined, and the quality and robustness of multi-modal image fusion under complex conditions are remarkably improved by decoupling content fusion and an illumination estimation task.

The present invention discloses a method for real-time global illumination rendering of a virtual cable tunnel scene model, comprising the following steps: using a computer to load panoramic image data and a three-dimensional scene model of the cable tunnel scene; calculating the position and radiation intensity of a light source in the three-dimensional scene model by using the panoramic image data, and thus obtaining the material properties of the three-dimensional scene model; reading in the triangular patches of the three-dimensional scene model; tracing the light rays emitted from the viewpoint to the screen pixels, and determining whether the light rays intersect with the triangular patches. If they intersect, the color value of the intersection point is calculated as the color value of the screen pixel according to the material properties of the intersection point. If they do not intersect, the background color is filled into the screen pixel, thereby completing the real-time global illumination rendering of the screen image to obtain a realistic screen image. It can realize the real-time global illumination rendering of the three-dimensional scene model of the virtual cable tunnel, effectively improve the efficiency of the global illumination rendering algorithm, and reduce the time cost.

The invention discloses an image shadow removal method based on multi-scale illumination decomposition, and belongs to the field of image processing, and the method comprises the steps: proposing an improved Retinex-based illumination decomposition network, and decoupling an input image into an illumination component representing illumination distribution and a reflection component containing the inherent texture of an object; a local illumination recovery method based on wavelet features is provided, frequency domain features are extracted by using multi-scale wavelet transform, weight distribution of a shadow area and a non-shadow area is dynamically adjusted through a wavelet attention mechanism, and global illumination consistency is ensured in combination with a reflection component; and a local detail enhancement method based on spatial domain features is provided, the image is further enhanced and refined by using the spatial domain features under the optimized illumination condition, and the texture authenticity of an output shadow removal result is ensured. According to the method and the device, end-to-end shadow removal of the input shadow image can be realized without depending on shadow position prior information, and a high-quality shadow removal result can be obtained.

The embodiment of the invention provides a global illumination rendering method and device, a GPU and a computer readable storage medium, and relates to the technical field of global illumination. Acquiring a plurality of local illumination models corresponding to the current frame; each local illumination model corresponds to one illumination probe, and the local illumination models are calculated by the CPU according to GI primitive parameters of adjacent grid units corresponding to the illumination probes; for each illumination probe in the current frame, performing iterative calculation according to a local illumination model of the illumination probe in the current frame and historical visibility information and historical illumination information of the illumination probe and an adjacent illumination probe of the illumination probe in the previous frame to obtain visibility information and illumination information of the illumination probe in the current frame; and performing global illumination rendering on the current frame according to the visibility information and the illumination information of each illumination probe in the current frame, thereby improving the operation performance and the picture effect of GI processing of the mobile terminal equipment.

The present invention relates to the field of image correction and proposes an image correction method, device, system, and storage medium. The method involves synchronously capturing a color image and three-dimensional point cloud data of a target object using an RGB-D sensor, constructing an elastic mesh model (including stiffness attributes), and achieving high-precision surface unfolding based on finite element analysis to generate a geometrically corrected image. Multispectral shadow separation and generative adversarial network (GAN) inpainting techniques are combined to eliminate occluded shadows and generate textures with consistent illumination. Finally, global illumination uniformity is optimized through dynamic compensation based on ambient light perception. This technical solution aims to reduce errors in unfolding correction of non-planar objects, efficiently distinguish between real content and shadow areas, adapt to dynamic ambient light changes in real time, and improve the ability to generate complex textures.

The invention discloses an image illumination anomaly processing method and device, electronic equipment and a storage medium, which are used for solving the technical problem that the processing effect and the real-time performance cannot be considered at the same time in the prior art. Comprising the following steps: acquiring a brightness component of an RGB image to construct a single-channel brightness matrix; marking an overexposure area and a low-illumination area of the single-channel brightness matrix and calculating a global illumination intensity index; adjusting bilateral filtering parameters according to the global illumination intensity index to adjust a single-channel brightness matrix, and generating a filtered brightness matrix; carrying out enhancement through a Retinex algorithm to obtain an enhanced brightness matrix; determining a key area according to the enhanced brightness matrix and generating a local processing strategy; performing two-layer wavelet transform on the RGB image to obtain a plurality of frequency band components; adjusting each frequency band component according to the global illumination intensity index and the local processing strategy; reconstructing and adjusting the frequency band component through wavelet inverse transformation to obtain a reconstructed RGB image; and converting the reconstructed RGB image into a target image in a preset format.

The present invention provides a color constancy method, system and storage medium based on polarization parameters, which relates to the technical fields of computer vision, image processing and color enhancement. First, a color cast image and a polarization image corresponding to the color cast image are collected, then the Stokes parameters of the polarization image are calculated, the polarization degree values corresponding to each pixel point are obtained based on the Stokes parameters, and then the effective pixel points of the color cast image are extracted through the polarization degree values. Then, the pseudo-gray pixels and gray pixels in the effective pixel points are distinguished and the gray pixel weights are obtained, and then the values of the gray pixels in the color cast image are weighted and averaged to obtain a global illumination color estimation for eliminating the illumination color of the color cast image. Finally, a colorless cast image is obtained, which can effectively eliminate the adverse effects caused by pseudo-gray pixels in the image on the illumination color estimation, and improve the accuracy and robustness of the color constancy algorithm.

The utility model relates to a laser demarcation device with a lamp strip, which comprises a demarcation device body, an accommodating caulking groove is arranged on the demarcation device body, a neon lamp strip assembly is arranged in the accommodating caulking groove, the neon lamp strip assembly is connected with an energy supply control port in the demarcation device body, and a light guide device is arranged at the front end of the neon lamp strip assembly. A covering assembly is distributed on the outer surface of the light guide device. Therefore, by selecting different covering assemblies, the neon lamp strip assembly can achieve different display effects such as overflow display, frosted soft light, global lighting and graphic display, and the requirements of decoration display and function display are met. The functions of the demarcation device body can be associated through different colors of the neon lamp strip assembly, for example, green is in a surveying and mapping state, red is in a charging state, blue is in a standby state and the like, so that a user can intuitively know the current state of the demarcation device body.

The invention discloses a complex-material-oriented multi-path full-frequency global illumination neural rendering method and system, and belongs to the technical field of computer graphics, and the method comprises the steps: carrying out the scene query of light emitted by pixels, and obtaining a primary geometric buffer and a multi-path mixed geometric buffer of the multi-time ejection of the light; respectively extracting main frequency features and multi-path sub-frequency features in a neural feature field based on the two features; performing directed graph structured modeling based on the multi-path sub-frequency features to obtain propagation features representing light path propagation information and global features representing overall light path information; performing multi-path frequency joint feature fusion based on the dominant frequency feature, the propagation feature and the global feature to generate a fusion feature with a full-frequency feature; and estimating a final radiation brightness value of the pixel based on the fusion feature, and completing neural rendering of global illumination. According to the method, efficient modeling and high-quality drawing of multi-path full-frequency global illumination under a complex material can be realized, and the sense of reality and dynamic consistency of a rendered image are remarkably improved.

This invention discloses a method and system for enhancing low-light underwater images, including constructing a low-light underwater image dataset, constructing a low-light underwater image enhancement network model, training the constructed low-light underwater image enhancement network model based on the low-light underwater image dataset, and finally using the trained low-light underwater image enhancement network model to predict low-light underwater image test samples to obtain high-quality underwater images, which are then evaluated using evaluation metrics. The solution of this invention employs a Retienx decomposition module based on deep learning, which effectively alleviates the specific scene limitations of pure physical algorithms. Utilizing a decoder feature module and a global illumination feature module, it promotes information interaction between encoding layer features and decoding layer features at the global level, thereby greatly improving the model's restoration capability. Extensive experiments have demonstrated the effectiveness of this method, and experiments on real low-light underwater image datasets show that the proposed method has good performance.