6results about How to "High sharpness" patented technology

The invention discloses an integrated fatigue small crack initiation in-situ monitoring device and a detection method, and belongs to the technical field of material mechanical property testing. Comprising a fatigue test system, a digital image correlation test system and an acoustic emission test system, the fatigue test system is used for detecting the fatigue performance of a sample under loading force in situ and comprises a console and an in-situ fatigue testing machine, and two tensile fixtures are symmetrically arranged on the in-situ fatigue testing machine; the digital image correlation test system is used for in-situ detection of time and space trajectories of crack initiation and expansion under fatigue of a sample, and comprises a camera, a bracket and an image acquisition card; the acoustic emission test system is used for in-situ detection of an accumulation process of internal damage of a sample under fatigue, and comprises an acoustic emission sensor, a preamplifier and an acoustic emission acquisition card. By simultaneously capturing and recording the mechanical response, the optical image and the acoustic emission signal of the sample in the fatigue test period, real-time in-situ monitoring of multi-source information such as mechanical, optical and acoustic emission is realized.

The invention discloses a floating imaging display device. The floating imaging display device comprises a light source module, a periodic optical structure and a barrier layer, the light source module is used for generating light. The periodic optical structure includes a plurality of lenses arranged adjacent to each other, and the light passes through the periodic optical structure and generates at least one floating image. The barrier layer is used for blocking or absorbing part of light, and the barrier layer is arranged between any two adjacent lenses of the periodic optical structure. The light emitting angle of the other part of light which is not blocked or absorbed by the blocking layer is between alpha and beta, and the following condition is met: alpha = tan-1 (d / h); and beta = 2tan-1 (d / 2h), where alpha is a lateral view angle, beta is a positive view angle, d is the maximum width of the light through hole corresponding to each lens, and h is the distance from the light source module to the light through hole.

The application belongs to the field of image vision technology, and discloses a sand-dust image sharpening method, system, medium, equipment and terminal. The improved automatic color scale algorithm is used to perform secondary distribution on image pixels, so as to reduce image color deviation. The gamma correction algorithm and the improved dark channel prior algorithm are combined to perform brightness compensation on each image pixel, so as to enhance image sharpness. The gray world algorithm is combined to balance image color, so as to realize sharpening of deep-concentration sand-dust images. The application can effectively improve sand-dust image quality, improve the definition and sharpness of degraded images, and realize sharpening of blurred images in sand-dust weather. The application can effectively improve the definition and sharpness of deep-degraded sand-dust images. The image collected in severe weather with large sand-dust can be restored to a clear image by the processing of the application, which has important practical significance for security monitoring, road monitoring, face recognition and the like.

This application provides a low beam headlight module and a vehicle headlight. The low beam headlight module includes: multiple light sources arranged at intervals along a first direction; the low beam lens includes a widening lens unit and an elbow lens unit, which are integrally formed structures. The widening lens unit and the elbow lens unit share a light-incident surface and a light-exit surface. The light-incident surface is arranged opposite to the multiple light sources along a second direction, and the light-exit surface is located on one side of the light-incident surface along a third direction; the widening lens unit is used to form a low beam widening light pattern, and the elbow lens unit is used to form a low beam elbow cutoff line light pattern. The low beam elbow cutoff line light pattern and the low beam widening light pattern are combined to form a low beam light pattern; the light-exit surface includes multiple sub-light-exit surfaces arranged sequentially along the first direction, and the distance between the root of each sub-light-exit surface and the light source in the third direction gradually increases along the first direction. The embodiments of this application can effectively improve the luminous efficacy of the low beam headlight module.

The invention discloses a Raw domain multi-frame image video super-resolution method, system and device and a storage medium, for a Raw domain sequence continuously shot by an imaging device at a high speed, multi-frame features in a Raw domain image sequence are extracted by using a window spatial domain attention-based Transformer architecture, and the multi-frame features are aligned to a unified position by using multi-scale optical flow-based deformable convolution, so that the super-resolution of the Raw domain multi-frame image video is realized. Multiple aligned frames are fused by using an inter-channel attention-based Transform architecture, super-resolution enhancement is performed on features obtained by fusion based on a convolutional neural network architecture, original information on a Raw domain is fully utilized, the imaging quality is superior to that of an RGB domain, the noise intensity in an image can be greatly reduced, and the definition and sharpness can be remarkably improved. And natural and rich details are recovered.

This application discloses an image processing method, apparatus, device, and readable storage medium, relating to the field of image processing technology. The method includes: acquiring a first image; determining frequency domain features corresponding to the first image; fusing the first image and the frequency domain features to obtain a second image; determining noise features in the first image based on the second image and the first image; and removing noise from the second image based on the noise features to obtain a third image. This method can improve the denoising effect of images.