Processing method, device, and equipment before display screen point-by-point correction, and storage medium

Abstract

The invention discloses a processing method, device, and equipment before display screen point-by-point correction, and a storage medium. The method comprises the following steps: obtaining an original pixel image brightness array and a corresponding actual pixel image brightness array after hardware adjustment under different impact factors, and generating a training sample set; constructing a convolutional neural network model for removing invalid information in pixel image brightness distribution by taking the original pixel image brightness array as input and the actual pixel image brightness array as output; training the convolutional neural network model by using the training sample set; inputting the pixel image brightness array to be processed into the trained convolutional neural network model for processing, and outputting effective pixel image brightness array information. In this way, a convolutional neural network model is constructed and trained, invalid information of a pixel array captured by a camera is deducted in an algorithm mode, then the tolerance of obtaining appropriate imaging is increased, and the erection time of a display screen before point-by-point correction is shortened.

Description

technical field [0001] The present invention relates to the field of display technology, in particular to a processing method, device, equipment and storage medium before point-by-point correction of a display screen. Background technique [0002] At present, before performing point-by-point calibration on LED or AMOLED displays (especially low-gray), under the condition of setting the focal length, in order to make each pixel not sticky and the saturation and image size are suitable, the lens must be corrected. The aperture, exposure time (shutter), distance between the camera and the display screen, focal length, etc. have to be adjusted back and forth, and the setup time is very lengthy. [0003] For example, traditional shooting of low-gray and useful pixel array brightness information, when the focal length is fixed, if the blue saturation is insufficient, the exposure time or the aperture will be increased to achieve a suitable saturation, but this will easily cause th...

AI Technical Summary

Problems solved by technology

In this way, the red, green, and blue pixels must not stick to each other in the end, and the individual saturation and image size must be within the appropriate range, resulting in extremely lengthy setup time.

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