Method and device for using neural network to correct white balance of images
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A neural network and convolutional neural network technology, applied in the field of digital image processing, can solve the problems of easy failure of white balance effect
Active Publication Date: 2018-01-12
CHANGSHA PANODUX TECH CO LTD
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[0006] In order to solve the technical problem that the white balance correction is easy to fail in the prior a
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specific Embodiment 1
[0082] The present invention uses a neural network to correct image white balance, figure 1 It is a system flowchart of an embodiment of the present invention, including the following steps:
[0083] S1: Acquire the original image containing the standard color card in the predetermined environment;
[0084] In the image acquisition step, a high-pixel camera is used for framing, and the predetermined environment includes indoor lighting with different color temperatures (international standard artificial sunlight D65, simulated sunlight D50, European, Japanese, and Chinese store light sources TL84, simulated American store lighting CWF, family hotel lights F, etc.) scenes and outdoor scenes in different weather (sunny, cloudy) and different time periods (morning, morning, noon, evening, etc.) in two groups, of which the number of different indoor scenes is not less than 100, and the number of different outdoor scenes is not less than 500, In order to make the shooting scene in...
specific Embodiment 2
[0122] Compared with Embodiment 1, the present invention also adopts a better prediction model, the difference lies in steps S2, S4, and S6.
[0123] S2. Perform parameter extraction and processing on the white color block of the standard color card in the original image to obtain a parameter value representing the color temperature of the ambient light source;
[0124] Specifically, extract the red R, green G, and blue B component values of the white color block in the original image, and calculate the average value of the red component avgR gt , the average value of the green component avgG gt , the average value of the blue component avgB gt , according to the red component average avgR gt , the average value of the green component avgG gt , the average value of the blue component avgB gt Calculate the red gain component gainR gt , blue gain component gainB gt ;The formula is as follows:
[0125] gahn R gt =avgG gt / avgR gt
[0126] gain B gt =avgG gt / avgB ...
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Abstract
The invention discloses a method and device for using a neural network to correct white balance of images, and belongs to the technical field of digital image processing. The method comprises the steps of 1, collecting an original image; 2, calculating parameter values of color temperature of an ambient light source; 3, preprocessing the original image and an image to be processed to obtain a preprocessed image and a second preprocessed image which are used for training respectively; 4, constructing a convolutional neural network model; 5, training the convolutional neural network model; 6, utilizing the convolutional neural network to calculate and obtain a red channel gain value (gainR) and a blue channel gain value (gainB); 7, utilizing the red channel gain value (gainR) and the blue channel gain value (gainB) to conduct white balance correction on the image to be processed, and obtaining a white balance image after correction. The method solves the technical problem that white balance easily loses efficiency in the prior art, the calculation speed of an algorithm is effectively increased, the accuracy is greatly improved, and the model is very good in robustness.
Description
technical field [0001] The invention belongs to the technical field of digital image processing, and in particular relates to a method and a device for correcting image white balance by using a neural network. Background technique [0002] The basic concept of white balance is: in the process of image processing, under any light source, restore the color of the image of the original material of the white object, remove the influence of the color temperature of the external light source on the image, so that it can be displayed as white on the photo. [0003] Current automatic white balance algorithms can be divided into two categories, including unsupervised and supervised algorithms. Unsupervised white balance estimates the color temperature of the light source by proposing a series of related assumptions. The calculation is simple, but this type of algorithm is closely related to assumptions. Unsupervised white balance algorithm, common white block assumption and gray wor...
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