Digital picture obscurity enhancement method for anastomosing a plurality of blurring operators
A fuzzy enhancement and digital image technology, applied in the field of image processing, can solve the problems of image loss, low grayscale information, and inability to process, and achieve the effects of reducing calculation, overcoming uncertainty, and good visual effects
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Publication Date
- 2011-06-22
- Estimated Expiration
- Not applicable · inactive patent
Smart Images
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Abstract
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. [...
Examples
Embodiment
[0037] Taking the input of a color image (in three channels of R, G, and B) as an example, the specific implementation of the present invention will be described below.
[0038] Carry out the fuzzy enhancement of image in the following steps in this embodiment:
[0039] Step 1: Determine the overall brightness level of the image. This step can be provided after the image to be enhanced is observed by human eyes, or can be given by a statistical analysis method (such as by calculating the size of the average brightness of the image, if the average brightness is small, it is considered dark, and if the average brightness is large, it is considered brighter) is given. Divide the brightness and darkness of the image into four levels (levels 1 to 4 represent the levels from dark to bright, level 1 is very dark, level 2 is generally dark, level 3 is generally bright, level 4 is very bright ), where grades 1 to 2 are for darker images, and grades 3 to 4 are for brighter images. As...