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Low-light image colorizing method based on multidimensional data association rules

A low-light image and multi-dimensional data technology, which is applied in the field of colorization of night vision images, can solve problems such as difficulty in obtaining colorization effects, high manual input requirements, and complex algorithms, so as to shorten the colorization time and improve the colorization effect Good, real-time effect

Active Publication Date: 2017-12-15
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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  • Low-light image colorizing method based on multidimensional data association rules
  • Low-light image colorizing method based on multidimensional data association rules
  • Low-light image colorizing method based on multidimensional 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 colorizing method based on multidimensional data association rules. The method includes the steps of excavating multi-attribute rules of low-light images, classifying the low-light images based on SVM by using a sample database formed by different objects in similar scenes, excavating the set of strong association rules between brightness and colors in the low-light images by using multi-attribute-rule-constrained Apriori optimization algorithm, introducing class label elements, and finally generating a brightness-class-color strong association rule set; low-light image colorizing based on rule mapping, extracting pixel brightness and affiliated class in the low-light images, mapping and generating R, G, B color components corresponding to each pixel based on excavated and generated strong association rule set, and generating a color picture. Through the method, color images with good coloring effect and high color reduction degree can be obtained, hardware conversion is facilitated, and real-time coloring effect can be realized.

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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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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