Low-light-level image enhancement algorithm based on parabolic function

A parabolic function, image enhancement technology, applied in the field of image processing, can solve problems such as contrast reduction, large amount of calculation, color distortion, etc., to achieve the effect of improving brightness, fast running speed, and fast processing speed

Active Publication Date: 2014-12-24
SOUTHWEAT UNIV OF SCI & TECH
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Problems solved by technology

[0006] The purpose of the present invention is to solve the problems of existing low-illuminance image enhancement algorithms, such as large amount of calculation, serious color distortion, and decreased contrast, and provide a low-illuminance image enhancement algorithm based on parabolic function

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  • Low-light-level image enhancement algorithm based on parabolic function
  • Low-light-level image enhancement algorithm based on parabolic function
  • Low-light-level image enhancement algorithm based on parabolic function

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Embodiment Construction

[0020] In order to better understand the present invention, the parabolic function-based adaptive low-light image enhancement algorithm of the present invention will be described in more detail below in conjunction with specific embodiments. In the following description, detailed descriptions of currently existing prior art may obscure the subject matter of the present invention, and these descriptions will be ignored here.

[0021] figure 1 It is a flow chart of a specific embodiment of the self-adaptive low-illuminance image enhancement algorithm based on the parabolic function of the present invention. In this embodiment, proceed according to the following steps:

[0022] Step 1, image acquisition: capture a low-light image I through the imaging device, such as figure 2 shown;

[0023] Step 2, obtain the brightness component V: convert the image obtained in step 1 to the HSV color space, and obtain the maximum value of the RGB component for each pixel, and obtain the bri...

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Abstract

The invention discloses a low-light-level image enhancement algorithm based on a parabolic function to overcome the defects that an existing low-light-level image enhancement algorithm is large in calculated amount, the color distortion is serious, and the contrast ratio is low. According to the algorithm, firstly, the illumination situation of an image is measured according to the distribution situation of a histogram; secondly, segmented parabolic functions with different parameters are adopted for images with different illumination classifications to carry out the self-adaptation illumination enhancement; thirdly, equivalent-ratio enhancement is carried out on RGB channels, the colors are kept unchangeable, and a primary enhancement image is obtained; to increase the speed, the image is converted to the YUV color space, only the luminance component Y is denoised through guiding filtering, and the RBG color space is restored; lastly, detail compensation is carried out on the filtered image to obtain the final enhancement image. According to the method, the visual effect can be effectively improved without losing the image information, and the effect is superior to the effect of other methods. According to the method, the enhancement effect on the low-light-level image is obvious, the processing speed is high, and the high practicality is achieved.

Description

Technical field: [0001] The invention relates to image processing technology, in particular to a low-illuminance image enhancement algorithm based on a parabolic function. technical background: [0002] In the application of image acquisition or video surveillance, low-illuminance situations such as night vision or backlight are often encountered. In this case, the contrast of the collected images is low, and the detailed information is seriously lost, which brings inconvenience to many tasks. The use of low-illuminance color image enhancement technology can effectively reduce the impact of low-illuminance environments on image or video acquisition devices, thereby effectively improving the performance of video surveillance, image recognition, computer vision and other systems under low-illumination conditions, and solving many working problems. Therefore, it is very necessary to study the enhancement of low-light images. [0003] At present, there are three main categories...

Claims

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Application Information

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IPC IPC(8): G06T5/00
Inventor 张红英王小元吴亚东刘言
Owner SOUTHWEAT UNIV OF SCI & TECH
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