Highly adaptive image contrast enhancing method based on data driving technology

Abstract

The invention discloses a content-based block adaptive image contrast enhancing algorithm to solve the problem that adaptive processing of various degraded images with different characteristics can not be achieved in the prior art by the adoption of the data driving idea. According to the method, by means of block analysis and processing, images are better processed by means of the details and local information of the images; a parameterized enhancement function is established and can change the characteristic of an enhancement curve by adjusting relevant parameters, and then a corresponding enhancement function curve is generated for each image according to the characteristic of the image; features relevant to the enhancement function are extracted through content analysis of image subblocks, and matched enhancement parameters are automatically generated according to the features and assigned to the enhancement function to enable the features of the images to be organically related with the characteristics of the enhancement function. By the adoption of the method, adaptive processing of various degraded images with different characteristics can be achieved without manual intervention.

Description

technical field [0001] The invention belongs to the field of information technology, in particular to a highly adaptive image contrast enhancement method based on data-driven technology. Background technique [0002] Images contain very rich information. According to statistics, visual information accounts for 80% of all information received by human beings, so images are very important media and methods of information transmission. Therefore, the research on image processing has been a hot spot for a long time. Image enhancement is to strengthen the useful information in the image. It can be a process of distortion. Its purpose is to improve the visual effect of the image. For the application of a given image, it aims to emphasize the overall or local characteristics of the image. The original unclear image becomes clear or emphasizes some interesting features, expands the difference between different object features in the image, and suppresses uninteresting features, the...

AI Technical Summary

Problems solved by technology

The existing image contrast enhancement algorithms are roughly divided into two categories, one is non-adaptive methods, such as histogram equalization algorithm, histogram specification method, etc. The disadvantage of this type of method is: usually only applicable to a certain type of image, widely Poor applicability, difficult to be promoted

There are more and more image enhancement algorithms with adaptive capabilities, including content-based multi-channel low-brightness image enhancement algorithms, weight distribution adaptive gamma correction contrast enhancement algorithms, but these algorithms still have some problems, such as weak enhancement effects, It is not effective for complex image processing with multiple characteristics, and the adaptability range is small, etc.

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