Optimization method of digital photo frame based on image processing

By analyzing the pixel and edge distribution states of images in digital photo frames, identifying and optimizing the required values, and adjusting the contrast and smoothing the image, the problem of inappropriate image contrast in digital photo frames is solved, and the visual effect and user experience of the image are improved.

CN119090850BActive Publication Date: 2025-04-04SHENZHEN QIUYU ELECTRONIC CO LTD
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Patent Information

Application Number
CN202411219329.7
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-09-02
Publication Date
2025-04-04
Estimated Expiration
2044-09-02

AI Technical Summary

Technical Problem

When present digital photo frames display images, there is a problem of inappropriate contrast, resulting in insufficient image display and poor user experience of viewing images.

Method used

By comprehensively analyzing the pixels and brightness of each block in the image, the pixel distribution state of the image is identified, and weighted calculations are performed in combination with the edge distribution state to obtain the optimized demand value. The image is contrast adjusted based on the optimization demand value and after adjustments apply a smoothing filter to optimize the image.

Benefits of technology

It realizes targeted optimization of the image, improves visual effects, ensures that the details of key areas in the image are retained and enhanced, avoids unnecessary adjustments, and meets the visual needs of users.

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Abstract

The invention relates to the technical field of image processing, and in particular to an optimization processing method for a digital photo frame based on image processing; by performing pixel distribution recognition and edge distribution recognition on each block of an image to obtain a pixel recognition value and an edge recognition value, the pixel and edge distribution states of the image can be accurately recognized and measured, and a comprehensive analysis is performed to identify an area with a high contrast adjustment requirement; by retrieving and analyzing the pixel distribution value and edge distribution value of each block in the image, the area to be adjusted can be accurately recognized, and the adjustment is performed in a targeted manner, the contrast of the image can be accurately optimized, and the brightness and contrast in the image can be effectively improved by adopting a local optimization method, so that the image effect is more ideal; applying a smoothing filter after contrast adjustment can reduce noise caused by over-sharpening, avoid unnatural noise or artifacts in the image detail part, and ensure that the image finally displayed is not only scientifically optimized, but also meets the visual requirements of users.
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