The invention discloses a high-precision image processing method and system based on illumination adaptive compensation, and relates to the technical field of computer vision and image processing, and the method comprises the steps: inputting an original image, and dividing the image into a high-frequency edge layer, an intermediate-frequency texture layer and a low-frequency illumination layer through a multi-scale residual network; acquiring illumination intensity, color temperature and scene categories in real time by using an ambient light sensor and a scene semantic segmentation model, and generating dynamic compensation parameters; carrying out dynamic range expansion on a low-frequency illumination layer based on a physical illumination model, and adjusting the weight of highlight suppression and dark area enhancement through a self-adaptive S-shaped exposure curve; a double-branchgenerative adversarial network is adopted, noise suppression and super-resolution reconstruction are carried out on the high-frequency layer, and texture detail enhancement is carried out on the intermediate-frequency layer; aligning the data of the depth camera and the infrared sensor with the visible light image through a cross-modal fusion module; and performing tone mapping on the fused image based on human visual characteristics, and outputting an enhanced image with a high dynamic range and reserved details.
The invention discloses an image enhancement method and system in a complex coal mine environment, and relates to the technical field of image processing, and the method comprises the steps: carrying out the preprocessing of a collected coal mine image of a target region, and dividing the coal mine image into different semantic regions, including a bright region, a dark region and a dust shielding region, through a deep learning semantic segmentation model; according to semantic region characteristics, a differentiation enhancement strategy is made; a traditional Retinex model is improved, non-local mean filtering is introduced, and an illumination component and a reflection component are decomposed through pixel similarity matching. According to the method, the image is divided into the bright area, the dark area and the dust shielding area through the deep learning semantic segmentation model, differential enhancement strategies are formulated according to different area characteristics, detail distortion caused by global adjustment is avoided, local contrast suppression is adopted in the bright area, illumination compensation is enhanced in the dark area, and the image quality is improved. Noisediffusion of the dust shielding area is inhibited through edge preservation smoothing, the image quality of each area is remarkably improved, and it is ensured that image details in a complex coal mine environment are clear and visible.
The invention provides an intelligent control method for a floodlight illumination system, and the method comprises the steps: obtaining an environment surface roughness coefficient, spectral reflection distribution and spatial geometric change data, determining the wall surface material absorptivity and shielding region coordinates, and obtaining environment reflection characteristics and shielding distribution data; analyzing shielding boundary sharpness and shielding angle distribution according to the spatial geometric change and the coordinates of the shielding area, calculating a luminous flux distribution curve of a local dark area, and judging whether the influence range of the dark area exceeds a preset threshold range or not; calculating the illumination coverage integrity according to the updated light field distribution and polarization reflection characteristics, determining the boundary sharpness of a light beam, and obtaining a light field uniformity parameter; and according to the light field uniformity parameter and the shielding thermal radiation effect, calculating and optimizing light field parameters.
The invention relates to a light spot uniformity optimization method and system for a high-precision VCSEL device, and the method comprises the following steps: carrying out the light field collection of a light-emitting surface of the VCSEL device, obtaining the intensity distribution of original light spots, analyzing the non-uniformity of each light-emitting unit, and extracting the non-uniformity characteristics of the light spots. And carrying out deviation cause analysis based on the characteristics, and identifying device structure deviation parameters. According to the method, an etching process is optimized, a corrected oxidized aperture configuration scheme is obtained, near-field light fieldsimulation is carried out by adopting a finite difference time domain method, and optimized light field distribution is verified and predicted. And finally, adaptive compensation design is carried out on the Bragg reflector structure based on a prediction result, light field regulation and control are realized, target light spot uniformity distribution is finally obtained, and the problem that systematic analysis and feedback control on non-uniformity causes of a light emitting unit layer in a device are lacked in the prior art is solved. And local bright spots or dark areas are caused.
The invention discloses a nighttime image enhancement method based on multidirectional information extraction and color loss optimization, which comprises the following steps: firstly, collecting nighttime and normal light road scene images, constructing a nighttime road image enhancement model based on deep learning, and adopting an image enhancement framework based on GAN and a superficial layer semantic enhanced U-Net network as a generator; the five-layer convolutional network is used as a discriminator, then horizontal-vertical bidirectional differential convolution is used to extract multi-directional information of the image, a local illumination attention module is used to balance dark area brightness and bright area overexposure, and finally an adaptive color loss function is used to recover original colors of the image. The method can effectively solve the problems of image quality reduction, detail loss, color distortion and the like under the low-illumination condition, and is particularly suitable for night scene visual perception improvement in the field of vehicle-assisted automatic driving.
The invention discloses a heat exchangerwelding seam image enhancementprocessing method, and belongs to the technical field of image processing, and the method comprises the steps: S1, collecting a heat exchangerwelding seam original image through a preset collection module, and converting the original image into a grayscale image; s2, a processing module is preset, the gray level image is segmented based on a preset dynamic threshold value, and a welding seam area image and a base metal area image are generated; s3, in the welding seam area image, generating a first enhanced image, a second enhanced image and a third enhanced image through a preset generation module; and S4, extracting a reference edge contour of the weld joint area image from the base metal area image, performing pixel-level fusion on the first enhanced image, the second enhanced image and the third enhanced image, and outputting a weld joint image. According to the method, the weld joint area is divided into the highlight area, the dark area and the middle area to be processed respectively, weld pool texture loss caused by strong reflection is effectively restrained, and the problem that details are lost in a highlight scene in an existing method is solved.
The invention discloses a multi-scale Retinex low-illumination image enhancement method based on modified bilateral filtering, and belongs to the field of digital imageprocessing. Aiming at the problems of insufficient image brightness, detail loss, noise interference and color distortion in a low-illumination environment, the invention provides an improved image enhancementalgorithm. First, the RGB image is converted into an HSV color space, and the luminance component (V) is separated for subsequent processing to avoid color distortion caused by direct processing of the RGB channel. And then, a corrected bilateral filtering function is adopted as a center surrounding function of a multi-scale Retinex method, a brightness component is enhanced, a halo phenomenon is suppressed, and meanwhile, detail enhancement of a dark region and excessive suppression of a bright region are realized in combination with an improved Gamma transformation function. And for the reflection component, non-local mean filtering denoising is utilized, and image edge details are enhanced in combination with a Laplace operator. In addition, the color of the enhanced image is ensured to be natural and consistent by adaptively adjusting the saturation component. Experimental results show that the brightness and definition of low-illumination images can be remarkably improved, detail information and visual impressions are improved, and the method is suitable for various scenes such as night monitoring, medical image processing and agricultural monitoring. The method has the advantages of being excellent in enhancement effect, high in halo suppression and small in color distortion.
The invention provides a floor wear resistance detection method and system, is applied to the technical field of floor wear detection, and reflects the wear resistance of a floor coating by obtaining the variation of porosity before and after floor wear. When the porosity after abrasion is obtained, a two-dimensional optical image of a to-be-detected surface is collected through multi-direction illumination, and the image is subjected to alignment processing. By analyzing the light and shade change information and the shadow form information of the dark area in different illumination directions, when the light and shade change information of the dark area changes along with the change of the position of the light source and the shadow form information shows the dynamic change of rotation or movement, it is judged that the hole is the floor hole. The discrimination mechanism based on the illumination dynamic change effectively solves the problem that a two-dimensional optical microscope scheme in the prior art cannot distinguish real pores and shallow scratches, and avoids misjudgment of scratches generated by a large amount of wear as pores, thereby significantly improving the accuracy of porosity calculation after wear.
The invention discloses a method for testing short-circuit current of a solar cell. The method comprises the following steps: acquiring a first corresponding relation between the photoluminescence intensity of a standard cell under standard illumination intensity and the electroluminescence intensity of the standard cell under open-circuit voltage; providing a battery piece to be tested; irradiating partial areas of the first surface of the to-be-measured battery piece through a plurality of light sources with different wavelengths, and measuring to obtain bright area luminous intensity of a light receiving area and dark area luminous intensity of a non-light receiving area under the irradiation of the light sources with different wavelengths; according to the first corresponding relation and the luminous intensity of each bright area, obtaining basic electroluminescence intensity corresponding to the luminous intensity of each bright area; obtaining the equivalent external quantum efficiency under the irradiation of each wavelengthlight source according to the basic electroluminescence intensity and the dark space luminescence intensity corresponding to each wavelengthlight source; constructing a wavelength-equivalent external quantum efficiency curve; carrying out integral calculation on the wavelength-equivalent external quantum efficiency curve to obtain short-circuit current density, and calculating the short-circuit current of the battery piece to be measured according to the area of the first surface.
The invention relates to a low-illumination image enhancement method based on multi-mode classification and brightness feedback, and belongs to the field of image processing. The method comprises the following steps of: firstly, training a network, constructing a multi-modal illumination prior feature of an image, inputting the multi-modal feature and a brightness score of the image into an illumination perception classification network, obtaining a local probability value of image brightness, adaptively selecting a local or global enhancement processing method, and generating a fusion weight; in the local enhancement processing, dark area details are enhanced through a multi-scale parallel and double-attention mechanism, in the global enhancement, the brightness is improved by using a symmetric coding-decoding structure and a residual attention block, and linear fusion is performed after the brightness is enhanced; then, the brightness evaluation value of the image is fed back through the lightweight brightness estimation network, and the brightness of the image is enhanced. And optimizing the training network according to the joint loss function of image processing. The method provided by the invention can enhance image texture details and improve image definition under a non-uniform illumination condition and an extremely low illumination condition.
The invention discloses an intelligent identification monitoring and cooperative emergency system, which comprises a main body case, a double-shaft rotating mechanism, an annular light supplementing assembly, an integrated base and an intelligent analysis module, and is characterized in that the main body case comprises a first rotating device, an imaging module and a second rotating device; the double-shaft rotating mechanism comprises a horizontal rotating shaft and a pitching adjusting shaft; the annular light supplementing assembly comprises a light supplementing lamp array and a honeycomb anti-dazzle cover. The integrated base comprises a communication gateway and an emergency controller; the intelligent analysis module comprises an edge calculation unit and a response priority unit. Therefore, the beam splitterprism fuses visible light and infrared thermal imaging coaxial acquisition, the electromagnetic shielding design of the double-shaft rotating mechanism is combined, the imaging precision and stability are improved, the annular light supplementing assembly, the three-color-temperature LED module and the edge calculation unit cooperate, illumination is dynamically adapted, dark space glare is eliminated, an emergency controller hardware-level linkage device triggers instructions according to priorities, and therefore the imaging accuracy and stability are improved. The response time is shortened.
The invention belongs to the technical field of computer vision and image processing, and discloses a low-light image enhancement method and system based on space-frequency domain feature resolution self-adjustment. According to the enhancement method, a feature splitting and splicing process, a space-frequency domain feature resolution self-adjusting network architecture based on an encoder-decoder framework, and a complete processing process from low-light image input to normal illumination image output are provided. According to the method, a multi-scale feature map is further flattened into a two-dimensional matrix, image restoration is carried out from features of different scales through a linear layer and a feedforward neural network, and the integrity of a receptive field is further kept; besides, after the important spatial features are extracted, frequency restoration is carried out on the important area, the common problem that the dark area is excessively enhanced and details of the bright area are lost is effectively solved, and the color fidelity and the structural integrity in the low-illumination scene are better.
The invention relates to a loudspeaker array multi-objective optimization method and system for sound field partition control, and the method comprises the steps: dividing a sound field region into a bright region and a dark region according to a hearing expectation; constructing a decision variable vector by taking the loudspeaker arrangement candidate points as decision variables; constructing a multi-objective optimization model of multiple objectives about decision variable vectors; solving the multi-objective optimization model by adopting a multi-objective genetic algorithm to obtain a Pareto optimal solution; constructing a linear weighted target planning model based on the expected values of the multiple targets, target function values of the multiple targets corresponding to the Pareto optimal solutions, and weight coefficients of negative deviation variables and positive deviation variables of the target function values relative to the expected values; and solving the linear weighted target planning model to obtain a Pareto optimal solution corresponding to the target function value when the linear weighted target planning model takes the minimum value, and obtaining the optimal position and number of the loudspeaker array. According to the invention, the optimal balance among multiple targets is realized, and the sound field partitioning effect is further improved.
Vehicle lighting control system, characterized in that it comprises the following: an image capture device configured to capture image information about a vehicle driving ahead; an electronic control unit of the image acquisition device, configured to determine relevant data of a front object based on the image information, wherein the relevant data includes size, position and speed of movement; a light controlsystem configured to determine the properties of the dark zone corresponding to the object in front, based on the vehicle's driving parameters and relevant data, where the driving parameters include the vehicle speed; a projector drive configured to control a projector to project a white screen and create a dark zone in an area of the foreground object based on the properties of the dark zone.
The invention relates to the technical field of artificial intelligence, and discloses a low-illumination scene-oriented unmanned aerial vehicle imaging data enhancement method, which comprises the following steps of: S1, acquiring unmanned aerial vehicle imaging data and constructing a training data set; s2, data preprocessing based on illumination partition; s3, constructing and training a data enhancement model; and S4, enhancing the imaging data of the unmanned aerial vehicle. The data preprocessing based on the illumination partition in the step S2 comprises the following steps: generating a low-illumination area mask and a medium-illumination area mask based on the brightness information of the low-illumination image; a Gaussian smooth convolution operation is applied to the low-illuminance region identified by the low-illuminance region mask to suppress noise, and an original value is reserved for the medium-illuminance region identified by the medium-illuminance region mask to generate a pre-processed image. The problems of low-illumination image noise amplification and detail loss are solved by generating low-illumination region masks and medium-illumination region masks and respectively adopting noise reduction and retention strategies, and the balance of dark region noise reduction and bright region detail protection is realized.
The utility model provides a multi-lamp-bead intelligent physical therapy lamp. The multi-lamp-bead intelligent physical therapy lamp comprises a control unit, a heat dissipation substrate and a plurality of illumination units. The lighting units are arranged on the heat dissipation substrate in an array mode. The lighting unit comprises a lens and at least two LED lamp beads with different lighting wavelengths, and the lens covers the at least two LED lamp beads; the control unit is electrically connected with the LED lamp beads; when the physiotherapy lamp illuminates, the control unit respectively sends control signals to the LED lamp beads with the same illumination wavelength. The technical problem that illumination is insufficient due to the fact that a dark area is prone to being generated when an existing physiotherapy lamp controls illumination is solved, and the technical effects that the illumination panel and the lens are fully utilized, and dark-area-free and multi-wavelength illumination control is achieved are achieved.
The invention discloses an ocular surface illumination treatment device and method, and belongs to the technical field of ophthalmologymedical equipment and treatment. The device comprises an infraredcamera module, a computer terminal analysis control module, an optical power detection module, a mechanical adjustment module, a safety switch module and an illumination module. Wherein the infraredcamera module comprises an infrared CCD (Charge Coupled Device) camera and a near-infrared light source which are arranged at a preset included angle and can collect eye images and transmit the eye images to the computer terminal, and the highest recording speed of the infrared camera module is not lower than 200 frames per second; and the computer terminal analyzes the image to obtain pupil positions, diameters and distances, and adjusts relative positions of a shielding device and a lens group in the light path of the illumination module, the axis of the light path and the distance between left and right lens cones, so that the central dark area of the annular light spot is matched and overlapped with the pupil. Eye images are collected and processed firstly, then light spots and the lens cone are adjusted, finally phototherapy and real-time monitoring are carried out, light can be prevented from entering the fundus, the treatment safety is improved, and the device is suitable for ocular surface diseases such as xerophthalmia.
The lamp comprises a lamp body and a light source, the interior of the lamp body is hollow, a cavity is formed in the lamp body, the inner wall of the lamp body is provided with a light inlet face and a light outlet face which are used for transmitting light, the inner wall of the lamp body is further provided with a first light reflecting face used for reflecting light, and the light outlet face is located on one side of the light inlet face; the light source is arranged on the lamp body, and the light-out end of the light source is opposite to the light-in face. Wherein at least part of the first light reflecting surface inclines towards the light emitting surface, and light rays emitted by the light source enter the cavity through the light inlet surface and are emitted from the light emitting surface after being reflected by the first light reflecting surface. According to the LED lamp, after light enters the cavity from the light inlet face, part of parallel light is firstly projected to the inclined face and is reflected by the inclined face to the end, away from the light source, of the light outlet face, a dark area appearing at the end, away from the light source, of the light outlet face due to light attenuation is filled, and the light of the light outlet face of the lamp is dispersed more evenly; therefore, a more uniform light emitting effect is obtained.
A device for image processing includes processing circuitry configured to perform black level remapping. To perform black level remapping, the processing circuitry is configured to: determine luminance values for pixels of a first image, wherein the pixels of the first image are based on color values of samples in each color frame of a plurality of color frames of the first image, wherein each color frame is associated with a different color; determine a first threshold based on the luminance values; determine a mapping curve based on the first threshold and a second threshold; apply the mapping curve to color values of a set of the samples in each color frame to generate black level remapped samples for each color frame, the set of the samples having a color value between the first threshold and the second threshold; and generate a second image based on the black level remapped samples.
The invention relates to the technical field of display, and discloses a brightness mapping method based on Mini LED backlight and a backlight system.The method comprises the steps that an input image is analyzed, and image features are obtained; according to the image features, adaptively dividing a dimming area; and for each dimming area, realizing conversion from pixel brightness to Mini LED backlight brightness through nonlinear mapping in combination with human visual characteristics. By analyzing the input image to obtain the characteristics, adaptively dividing the dimming area and combining the human eye visual characteristics to carry out nonlinear mapping, the contrast ratio of the display image is effectively improved, the image details are reserved to the maximum extent, the image quality problem caused by dark area detail loss and bright area overexposure is remarkably improved, and the display effect better meets the human eye visual requirements.
The invention provides a thick-wall part optical system for eliminating dark areas on a side wall and a vehicle signal lamp, the thick-wall part optical system comprises a PCB, a thick-wall part and a plurality of LED light sources, the LED light sources are sequentially arranged on the PCB at intervals, the total reflection surface of the thick-wall part is a total reflection pattern surface, total reflection patterns are arranged on the total reflection pattern surface in an array mode, and the thickness of the thick-wall part is smaller than that of the PCB. The total reflection pattern surface is sequentially divided into a plurality of total reflection areas in the arrangement direction of the LED light sources, total reflection patterns between the adjacent reflection areas are continuously arranged, and each total reflection area is used for totally reflecting incident light emitted by the corresponding LED light source; incident light is totally reflected through the total-reflection patterns to form total-reflection light, and the total-reflection light is emitted through the light-emitting face of the thick-wall piece. The LED side wall is simple in structure, the total reflection pattern surface is divided into continuous total reflection areas corresponding to different LED light sources, the whole total reflection surface is evenly lightened at multiple angles, the problem of dark areas caused when the side wall is lightened is solved, efficiency is guaranteed, and the whole light emitting surface is evenly lightened.
The invention discloses an image processing method, an electronic device, a vehicle and a storage medium. The method comprises the following steps: identifying a dark area and a bright area in a preview image; determining a surrounding exposure parameter, the surrounding exposure parameter including a long exposure parameter, an appropriate exposure parameter and a short exposure parameter, the long exposure parameter being determined based on a dark area of the preview image, and the short exposure parameter being determined based on a bright area of the preview image, the appropriate exposure parameter is determined based on an initial exposure parameter of the preview image. The image obtained based on the long exposure parameter can reflect the details of the dark area, the image obtained based on the short exposure parameter can reflect the details of the bright area, the appropriate exposure parameter can accurately present the details and layers in the picture, and the imaging effect and the imaging quality of the preview image are ensured, namely, the image can be displayed in the dark area. The details from the shadow part to the highlight part in the scene to be shot can be captured based on the surround exposure parameters, the accuracy is high, and the use experience of a user can be ensured.
The invention relates to the technical field of image data processing, in particular to an impurity identification method and system for fruit and vegetable powder, and the method comprises the steps: collecting a fruit and vegetable powder image on a conveying belt, preprocessing the image into a gray-scale map, and calculating a dark channel index based on the gray-scale distribution characteristics in a neighborhood window to preliminarily screen a dark region; counting dispersion of gradient amplitude and information entropy of gradient direction in a pixel point neighborhood window, distinguishing smooth shadow and rough impurities by using the dispersion and the information entropy, and correcting a dark channel index to obtain impurity confidence; constructing a local histogram by using the impurity confidence as a weight, and carrying out adaptive weighted histogramequalizationprocessing on the grey-scale map to enhance the impurity contrast and suppress the shadow; and completing impurity identification through Otsu threshold segmentation and connected domain analysis. According to the method, the problem that shadow is easily misjudged as impurities when accumulated powder is processed by a traditional algorithm is effectively solved, and the detection accuracy is improved.
The invention relates to the field of car lamps, and discloses a car lamp diffuse reflection optical structure which comprises a light source, a light guide plate, a light guide plate and a light guide plate. The light guide structure is mounted in the automobile lamp shell, is arranged on a light emitting path of the light source and is used for receiving light of the light source and changing the propagation direction of the light; the diffuse reflection structure is installed in the automobile lamp shell and used for receiving the light processed by the light guiding structure, the light is scattered multiple times through surface textures, and diffuse reflection light spots evenly scattered to the visual face are formed. According to the invention, through the multi-stage scattering design of the thick-wall condenser, the dodging sheet and the frosted reflector, the light forms a uniform diffuse reflection effect without obvious light spots and dark areas on a visual surface, no granular sensation is generated when the light is lightened, the light is uniformly diffused according to the diffuse reflection principle, the direct strong light caused by the traditional mirror reflection is avoided, and the brightness of the light source is improved. And glare interference to drivers of vehicles and pedestrians is reduced.
The invention provides a transparent antenna lens and intelligent glasses, and belongs to the technical field of intelligent glasses. The antenna transparent substrate is arranged on the lens body. The plurality of first metal structures are arranged on the surface of the antenna transparent substrate and are far away from the lens body, so that the lens body and the transparent antenna are combined and can support each other, and the transparent antenna is arranged on the lens of the glasses. The design space of the transparent antenna is not limited by the size of the glasses legs any more and is far away from the head of the human body, the problem that the electromagnetic performance is low due to the fact that the human body absorbs and scatters electromagnetic waves and is limited by the size is solved, and the electromagnetic performance of the transparent antenna is greatly improved. The multiple first metal structures are connected and surround to form the irregular polygonal metal grid, so that the problems of bright diffraction fringes and dark areas caused by coherent interference generated by the periodic metal grid can be solved, and a user can see a clearer and more accurate image.