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A colorization method of low-light image based on multi-dimensional data association rules

A low-light image, multi-dimensional data technology, applied in the field of night vision image colorization, can solve the problems of difficult to obtain colorization effect, high manual input requirements, complex algorithm, etc., to shorten the colorization time and colorization effect. Good, real-time effect

Active Publication Date: 2020-10-02
NANJING UNIV OF SCI & TECH
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Problems solved by technology

The color diffusion method based on manual strokes requires manual input from the user, and the user's manual input is very demanding. Generally, it needs repeated operations many times to obtain the ideal colorization effect; the color transfer method based on the reference color image is complex and time-consuming. More, and it is difficult to get the ideal colorization effect

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  • A colorization method of low-light image based on multi-dimensional data association rules
  • A colorization method of low-light image based on multi-dimensional data association rules
  • A colorization method of low-light image based on multi-dimensional data association rules

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Embodiment 1

[0042] combine Figure 1~2 , the steps of the low-light image colorization method based on multidimensional data association rules proposed by the present invention are as follows:

[0043] Step 1: Mining multi-attribute rules of low-light images.

[0044] The Apriori optimization algorithm constrained by multi-attribute rules is used to mine the strong association rule set between brightness and color in the reference color image, and the category label element is introduced to finally generate the brightness-category-color strong association rule set;

[0045] For the mining of strong association rule sets, the present invention first extracts the brightness y of each pixel in the reference color image and its corresponding color components R, G, and B, and proposes an Apriori optimization algorithm constrained by multi-attribute rules. A "brightness-color" strong association rule set is established. After experiments, it was found that the generated "brightness-color" str...

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Abstract

The invention discloses a low-light image colorization method based on multi-dimensional data association rules. The steps of the method are as follows: Mining multi-attribute rules of low-light images: firstly, using the sample library composed of different objects in similar scenes, the low-light images are classified based on SVM, and the Apriori optimization algorithm constrained by multi-attribute rules is used to mine the reference color images. A strong association rule set between brightness and color, and introduce category label elements to finally generate a brightness-category-color strong association rule set; colorization of low-light images based on rule mapping: extract the brightness and category of pixels in low-light images , based on the strong association rule set generated by mining, map and generate the R, G, and B color components corresponding to each pixel to generate a color map. The method of the invention can obtain a color image with good colorization effect and high color restoration degree, and the method is easy for hardware conversion, and can realize real-time colorization effect.

Description

technical field [0001] The invention belongs to the technical field of night vision image colorization, in particular to a low-light image colorization method based on multidimensional data association rules. Background technique [0002] Low-light image colorization has always been a research hotspot in night vision technology. The low-light image is the result of photoelectric device imaging, usually a grayscale image. Combined with the characteristics of higher resolution and sensitivity of the human eye to color images, the colorization of low-light images can improve people's cognition of target and scene information , both in the military and civilian fields are of great significance. [0003] At present, the methods for colorizing grayscale images mainly include color diffusion methods based on manual strokes and color transfer methods based on reference color images. Based on the assumption that "if spatially adjacent pixels have similar brightness, their colors wi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T3/00G06K9/62
CPCG06F18/2411G06T3/10
Inventor 陈冬冬张炜韩静柏连发张毅
Owner NANJING UNIV OF SCI & TECH
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