12results about How to "Improve local contrast" patented technology

The invention discloses a diseased fish detection method and device, and belongs to the technical field of computer vision detection. In order to solve the problems that in the prior art, diseased fish disease detection efficiency is low, accuracy is not high, and real-time detection cannot be achieved, a diseased fish detection model is constructed, and the diseased fish detection model comprises a backbone network, a neck network and a detection head network; the method comprises the following steps: inputting a diseased fish image into a backbone network based on a spatial deep convolutional neural network for feature extraction to obtain a visual feature map, and then inputting the visual feature map into a contrast-enhanced attention transfer structure of a neck network for feature fusion processing to obtain a fused feature map; and the fusion feature map is input into a detection head network, and a sick fish target detection result is obtained through detection of a multi-head prediction small target detection algorithm, so that fish school disease detection is performed in real time, the detection efficiency and detection precision of fish diseases are effectively improved, and the method has relatively high practicability and application universality.

The invention discloses a screen copying identification method, device and equipment, and the method comprises the steps: carrying out the LBP feature extraction of a target image through a plurality of preset pixel radiuses, and obtaining a plurality of LBP feature data sets; scaling the target image by using a scaling factor to obtain a target scaled image under the scaling factor; for each target scaled image, executing the steps S131-132: S131, performing edge detection and frequency domain analysis on the target scaled image to obtain the moire feature and moire intensity of the target scaled image; s132, inputting a plurality of LBP feature data sets and the moire features and moire intensity of the target scaled image into a preset multi-feature input convolutional neural network to obtain a copying probability and a non-copying probability of the target scaled image; and determining whether the target image is copied or not according to the copying probabilities and the non-copying probabilities of the plurality of target scaled images. The invention belongs to the field of image copying recognition. According to the invention, the accuracy of image copying identification can be improved.

This application provides an image processing method, apparatus, device, storage medium, and program product. The method includes: acquiring an RGB image; converting the RGB image into a luminance image; determining a luminance gain value for each pixel in the RGB image based on the luminance image; and processing the RGB image based on the luminance gain values ​​to obtain a processed RGB image. This improves the local contrast of the image.

This invention belongs to the field of underwater robot control technology, specifically providing a dual-field-of-view cooperative perception and adaptive weighted localization method and system for underwater robots in confined spaces. The method utilizes a pre-calibrated heterogeneous dual-field-of-view camera system on the robot to acquire main and auxiliary field-of-view images. Image enhancement is performed through red channel compensation and contrast-limited adaptive histogram equalization, and image quality indices are calculated. An analytical pose estimation algorithm based on microplanes is employed to detect visual markers and calculate their poses, obtaining two sets of camera pose observations. The two sets of observations are then weighted and fused using calculated fusion weights to obtain the robot's center visual pose. An error-state Kalman filter is constructed, using the visual pose as the observation input, and dynamically adjusting the observation noise covariance matrix based on the fusion weights to output the final pose. This invention can achieve highly robust and high-precision localization in complex underwater environments.

The present invention discloses an aviation airborne navigation image target recognition method based on spatial entropy harmony search. The method utilizes the position distribution information of the image grayscale space to calculate the image grayscale space distribution entropy value, and maps it into a uniform distribution function. The function is then processed by 2D-DCT, transform system weighting and inverse 2D-DCT linear transformation to achieve simultaneous enhancement of the global and local contrast of the original image. The method is combined with the maximum entropy harmony search algorithm. Although the method is similar to the genetic algorithm, it adopts a multi-point mating mode in the process of searching for new solutions in the field, so that the new solutions are more diverse and the possibility of the algorithm jumping out of the local optimal solution is improved.

This invention discloses an image processing method based on wavelet transform, belonging to the field of image processing technology. The method includes: converting the RGB values ​​of the acquired image to Lab space and separating the L, a, and b channels; selecting wavelet transform and choosing the order of wavelet transform according to the image size; applying wavelet transform to the L channel to obtain the image coefficients of each layer; calculating the mean and variance of the image coefficients of each layer; and calculating the adjustment coefficient G of each layer. i The adjustment coefficient G is applied to each layer of the wavelet-transformed image. i Apply adjustment factor G to each image layer. i Then, an inverse wavelet transform is performed to recover the L channel; the processed L channel is restored to the range of [0,255]; the L, a, and b channels are merged and converted to RGB space to obtain the processed image; this method preserves the local details of the image, improves noise robustness, and improves computational efficiency.

The invention relates to the technical field of ultrasonic image processing, and the method comprises the steps: carrying out the calculation of three different feature algorithms on an obtained ultrasonic training image, thereby obtaining a clear ultrasonic feature point image; processing the ultrasonic training image based on a preset first feature algorithm to obtain a first ultrasonic image, processing the first ultrasonic image based on a preset second feature algorithm to obtain a second ultrasonic image, and processing the second ultrasonic image based on a preset third feature algorithm to obtain an enhanced ultrasonic image, the ultrasonic training image is processed through the obtained enhanced ultrasonic image and the initial feature extraction model to obtain the initial feature image to determine the loss function, and the quality of the 2D feature points can be improved through the three feature algorithms, so that the problem that the extraction of the 2D ultrasonic image feature points is not accurate enough is solved.

This invention discloses a driving method and system for a transparent LCD display based on local dimming, relating to the field of local dimming technology for transparent LCD displays. The method includes: dividing the transparent LCD display into multiple driving zones and collecting the ambient light intensity of each driving zone; establishing a transparent display optical perception model; extracting a set of perception indicators; performing driving solution and outputting a combination of driving parameters for each driving zone; and executing a fusion drive of the transparent LCD display according to the multiple driving parameter combinations. This invention solves the technical problem in existing technologies where the driving of a transparent LCD display is difficult to adapt to the differences in ambient light and dynamic changes in image perception, resulting in poor coordination of display brightness, transparency, and local contrast, and insufficient driving accuracy. It achieves precise driving of each driving zone of the transparent LCD display to adapt to the needs of ambient light and image perception, improving the synergistic optimization effect of display brightness, transparency, and local contrast.

This invention relates to the fields of optical imaging and intelligent image processing technology, and discloses a dual-modal image fusion enhancement method, system, device, and storage medium. The method includes: acquiring initial dual-modal images obtained through coaxial synchronous transient acquisition of the same scene; fusing the initial dual-modal images based on a saliency matrix; performing differentiated adaptive noise reduction processing on the low-frequency and high-frequency components separated from the fused image; performing dynamic anti-reflection compensation processing on the reconstructed high- and low-frequency images; performing a two-dimensional fast Fourier transform and centering the spectrum; constructing a notch mask and a low-frequency protection region at the center of the spectrum to suppress the narrow-band energy peak when a narrow-band energy peak corresponding to sensor row and column noise is identified; and then performing an inverse Fourier transform to output the enhanced image. Through the above methods, this invention can improve image sharpness, local contrast, and stripe suppression, while reducing artifacts generated during the enhancement process.

The application relates to the technical field of image data processing, in particular to a geological remote sensing interpretation method and system for mineral resource exploration, which comprises the following steps: acquiring a geological remote sensing image to be analyzed in a mineral resource area; analyzing the uniformity of the distribution of the pixel gray value of all local areas in the image to be analyzed to obtain the image smoothness; acquiring the LBP value of all pixel points in the image to be analyzed and a historical standard sample image and performing clustering; using a seed growing algorithm to obtain each growth area of each image; determining an image detail evaluation index of the image to be analyzed through the overall distribution of the edge complexity of the growth area of each cluster to which the image to be analyzed and the historical standard sample image belong, obtaining an image enhancement effect quality evaluation, adjusting the wavelet threshold in combination with the image detail evaluation index, and interpreting the enhanced image. The application aims to improve the accuracy of geological remote sensing image interpretation in mineral resource exploration.

The application provides an improved CLAHE short-wave infrared image real-time enhancement method based on FPGA. In view of the problems of low contrast, unobvious detail information and easy amplification of noise of InGaAs short-wave infrared imaging under low illumination, an improved limited contrast adaptive histogram equalization image enhancement algorithm is provided, and the optimal clipping threshold is automatically determined through an adaptive search mechanism, so that the local contrast is enhanced and the noise amplification is inhibited. The application can effectively improve the contrast and detail distinguishability of the short-wave infrared image, reduce the influence of noise, and is suitable for fields of short-wave infrared imaging systems, target identification systems and weak light vision systems.

The present invention relates to a method and system for adjusting the backlight brightness of a display screen based on Mini QLED technology. The method: divides a display image signal into a brightness signal, a chromaticity signal and a saturation signal, and generates image feature data; performs sub-pixel boundary detection to obtain multiple initial backlight sub-regions, and calculates regional brightness distribution data; performs regional clustering operations and regional merging to obtain multiple target backlight sub-regions and calculates backlight partition mapping data; performs nonlinear feature transformation, and calculates the backlight unit control data of the Mini LED backlight unit; uses a deep Q network to output the backlight compensation amount of each of the target backlight sub-regions; performs real-time feedback correction, calculates the deviation value between the actual display parameters and the target parameters of each target backlight sub-region, and outputs a backlight optimization control signal. The implementation of the present invention realizes the precise adjustment of the backlight brightness and improves the consistency of the display effect.