An intelligent image recognition repair processing system and method based on big data

The intelligent image recognition and restoration system based on big data solves the problems of high computational load and slow restoration speed in existing technologies, achieving efficient and high-quality image restoration results and improving user experience and restoration efficiency.

CN121073833BActive Publication Date: 2026-05-08NANJING LEZHI INFORMATION TECH CO LTD
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Patent Information

Application Number
CN202511166052.0
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-08-20
Publication Date
2026-05-08
Estimated Expiration
2045-08-20

AI Technical Summary

Technical Problem

Existing technologies for image restoration are computationally intensive, require a lot of data, and are slow to restore, making them difficult to apply in real time. Traditional texture diffusion techniques can easily lead to blurred textures or structural distortions in the restored image, and image restoration has a significant impact on user experience.

Method used

An intelligent image recognition and restoration system based on big data is adopted, including an image verification module, a selection restoration module, a grayscale restoration module, a color separation enhancement module, and a color mixing filtering module. Data loss is detected by check code, local restoration is performed using a pre-trained model, grayscale diffusion and color separation processing are performed, and image restoration is achieved by combining different filters.

Benefits of technology

It reduces image transmission pressure, minimizes data block effects and color distortion caused by network fluctuations, significantly improves user visual experience and repair efficiency, and adapts to the repair needs of different devices and scenarios.

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Abstract

The application relates to the field of image restoration, in particular to an intelligent image recognition and restoration processing system and method based on big data, which comprises an image verification module, a selection restoration module, a gray scale restoration module, a color separation enhancement module and a color mixing filter module; the image verification module is used for determining image information loss; the selection restoration module is used for calculating the peak signal-to-noise ratio of the image; the gray scale restoration module is used for outwardly extending the gray scale texture of the image; the color separation enhancement module is used for separating the image colors by using different color separation schemes; and the color mixing filter module is used for carrying out image denoising and image color mixing processing through a filter. The application can avoid the data block effect, blurring and color distortion caused by network fluctuation, reduce the image restoration time, adapt to the viewing demand of users, reduce the influence of data loss on the image, optimize the calculation efficiency of the restoration algorithm, improve the picture texture visual sense and improve the visual experience of terminal users.
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