Digital picture obscurity enhancement method for anastomosing a plurality of blurring operators

Abstract

The invention discloses a digital image fuzzy intensification method for inosculating a plurality of fuzzy operators. The method is divided into four steps: step one, brightness-darkness grades are defined as four grades; step two, for a first grade image and a second grade image , a linear transit function is adopted to make conversion, for a third grade image and a fourth grade image, a nonlinear transit function is adopted to make conversion; step 3, on a fuzzy field, different brightness-darkness grades choose different fuzzy operators to make fuzzy image intensification: for the first grade image, a multinomial intensification operator is adopted to make fuzzy field intensification; for the second grade image, a logarithm type intensification operator is adopted to make fuzzy field intensification; for the third grade image and the fourth grade image, a sectional transit type intensification operator is adopted to make fuzzy field intensification; step 4, inverting back to null-field, fuzzy intensified null-field images are obtained and sent out. The invention can get a better visual efficiency whether the image is of insufficient exposure or over exposure.

Description

technical field [0001] The present invention relates to an image processing technology in the field of chip design, in particular to a digital image fuzzy enhancement method fused with multi-fuzzy operators, that is, an image enhancement method realized by fuzzy set theory, which can be used to process black-and-white and color images . Background technique [0002] At present, the application of image processing in chip design is more and more extensive, such as: digital camera, digital video camera, mobile phone, video conferencing system and so on. Image processing generally includes preprocessing, compression, and postprocessing. Image enhancement technology is a commonly used method in image preprocessing. Its purpose is to selectively highlight or weaken certain information in the image for a given image according to specific needs, so as to improve the visual effect of the human eye, or Convert images to human-eye observation or machine analysis and processing. [...

AI Technical Summary

Problems solved by technology

[0005] The traditional fuzzy enhancement method has the following defects: (1) Due to the limitation of the selected fuzzy membership function, the image after fuzzy enhancement loses part of the low gray level information

(2) Enhance the entire grayscale area of ​​the image, and cannot process several grayscale levels of interest

(3) For different images, the traditional fuzzy enhancement only uses the same fuzzy enhancement operator to enhance the digital image, and it cannot achieve better visual effects for images of various bright and dark levels.

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