Backlight image enhancement and denoising method based on foreground-background separation

An image enhancement, foreground background technology, applied in the field of backlight image enhancement and denoising, can solve the problems of increasing the difficulty of backlight image, enhancing the details of foreground area, and unable to enhance and denoise backlight image.

Active Publication Date: 2016-06-08
GUANGDONG XUNTONG TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the processing of backlit images is still a difficult problem without a mature solution
Complex lighting conditions greatly increase the difficulty of backlight image processing
Traditional image enhancement methods often cause the details of the foreground area of ​​the backlit image to be enhanced insignificantly, while the background area is over-enhanced. At the same time, the backlit image has different noise levels in the

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  • Backlight image enhancement and denoising method based on foreground-background separation
  • Backlight image enhancement and denoising method based on foreground-background separation
  • Backlight image enhancement and denoising method based on foreground-background separation

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Embodiment Construction

[0076] refer to figure 1 , the present invention provides a backlight image enhancement and denoising method based on foreground and background separation, comprising:

[0077] S1, using an interactive matting algorithm to divide the backlight image into a foreground area and a background area;

[0078] S2, using the improved Retinex algorithm to enhance the pixels in the foreground area;

[0079] S3. Using the CLAHE algorithm to equalize the pixels in the background area;

[0080] S4. Using a multi-scale NLM algorithm to denoise the enhanced foreground area and the equalized background area;

[0081] S5. After performing weighted fusion of the noise-reduced foreground area and the background area, an enhanced and noise-reduced backlight image is obtained.

[0082] Further as a preferred embodiment, the step S1 includes:

[0083] S11, converting the backlight image into a grayscale image;

[0084] S12. After extracting rough foreground contours and background contours of ...

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Abstract

The invention discloses a backlight image enhancement and denoising method based on foreground-background separation. The backlight image enhancement and denoising method comprises the steps that a backlight image is divided into a foreground area and a background area by adopting an interactive cutout algorithm; the pixel points in the foreground area are enhanced by adopting an improved Retinex algorithm; equalization processing is performed on the pixel points in the background area by adopting a CLAHE algorithm; denoising is performed on the foreground area after enhancement and the background area after equalization processing by adopting a multi-scale NLM algorithm; and weighted fusion is performed on the foreground area and the background area after denoising so that an enhanced and denoised backlight image is obtained. Different enhancement and denoising methods are respectively adopted for the foreground area and the background area of the backlight image so that detail enhancement of the foreground area of the backlight image can be realized, the background area can be protected from being excessively enhanced, the denoising effect is great and accuracy is high and thus the backlight image enhancement and denoising method can be widely applied to the field of backlight image processing.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a backlight image enhancement denoising method based on foreground and background separation. Background technique [0002] Glossary: [0003] Retinex algorithm: Retinex is the abbreviation of "Retina" (retina) and "Cortex" (cerebral cortex). The Retine algorithm is an image enhancement algorithm based on the human visual system based on scientific experiments and scientific analysis. It can achieve a balance in dynamic range compression, edge enhancement and color constancy, and adapt to various types of images. sexual enhancement; [0004] CLAHE algorithm: Contrast-limitedAdaptiveHistogramEqualizationalgorithm, limited contrast adaptive histogram equalization algorithm; [0005] NLM algorithm: Non-Local Means algorithm, non-local average image denoising algorithm, estimates the center point of the reference block by weighting the self-similar structural block, thereby reducin...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06T7/00
CPCG06T5/002G06T2207/20182
Inventor 夏志强刘峰干宗良吕月圆陈色桃
Owner GUANGDONG XUNTONG TECH
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