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A single image, image technology, applied in the field of computer vision, can solve the problem that the running speed needs to be improved, and achieve the effect of reducing the computational complexity, improving the speed, and ensuring the rationality
Active Publication Date: 2013-05-29
TSINGHUA UNIV
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In addition, a scholar named Tarel proposed a faster dehazing algorithm in 2009, but in general, the running speed of all the above dehazing algorithms needs to be improved
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Embodiment 1
[0057] figure 1 It is a flow chart of the present invention for color image defogging
[0058] This embodiment is used to process color images, and the steps are as follows:
[0059] 1) Obtain a color original image, and obtain the luminance matrix (also called the minimum luminance matrix) of the original image according to the values of the red, green, and blue color channels of the original image.
[0060] Read in a foggy color image, denoted as I, the pixel value at the coordinate x of the color image is denoted as I(x), and the image pixel value range is between 0-255;
[0061] For the pixel value I(x)=[Ir(x) at this color image coordinate x, I g (x), I b (x)], I r (x), I g (x), I b (x) represents the value of the coordinate x in the three color channels of red, green and blue, and the lowest brightness matrix of the original color image is obtained according to the values in the three color channels.
[0062] Preferably, take the minimum value of the coordinat...
Embodiment 2
[0107] figure 2 It is a flow chart of the present invention for grayscale image defogging
[0108] Dehazing of grayscale images is a simplified special case of color images.
[0109] 1) Obtain a grayscale original image, and obtain the brightness matrix of the original image.
[0110] Read in a foggy grayscale image, denoted as I(x), the image pixel value range is between 0-255, and the brightness matrix obtained is preferably the pixel value matrix of the grayscale image itself.
[0111] 2) Carry out a median filtering operation on the luminance matrix to obtain a median filtering matrix.
[0112] Median filtering is performed on the matrix I(x), and the formula is as follows:
[0113] I med (x) = median sv (I(x)) (7)
[0114] Among them, sv is the radius of the median filter;
[0115] 3) Obtain the atmospheric light value based on the luminance matrix and the median filter matrix.
[0116] Find the maximum value of all elements of I(x), denoted as A I , get I med ...
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Abstract
The invention discloses a method for quickly demisting a single color image and a method for quickly demisting a single gray level image. The method for demisting a single color image comprises the following steps of: obtaining an original image and obtaining a brightness matrix according to the original image; performing median filtering operation on a lowest-brightness matrix to obtain a medianfiltering matrix; obtaining an atmosphere light value based on the lowest-brightness matrix and the median filtering matrix; multiplying the median filtering matrix, the lowest-brightness matrix and the atmosphere light value with a preset proportionality factor and selecting a minimum value serving as an atmosphere dissipation function; and obtaining a demisted image based on the original image,the atmosphere light value and the atmosphere dissipation function. The method for demisting a single gray level image is a special case of the method for demisting a single color image. According tothe demisting method provided by the invention, the demisting operating speed of a single image can be increased, the demisting method can be applied to certain systems with high requirement on instantaneity, and time is won for subsequent processing.
Description
technical field [0001] The invention relates to a method for clearing images in the field of computer vision, in particular to a method for clearing images in foggy days, and in particular to a method for quickly defogging single images. Background technique [0002] When capturing images under severe weather conditions, a large number of particles suspended in the atmosphere (such as fog and haze) will absorb and scatter light, resulting in a decrease in the quality of the captured image, such as blurred images, color distortion, and decreased contrast. It not only reduces the visibility of the image, but also makes it difficult for subsequent image processing algorithms (such as object recognition, feature extraction, image analysis, etc.). [0003] At present, the defogging algorithms proposed by domestic and foreign scholars in the field of computer vision can be divided into two types based on multiple images (or other additional information) and based on only a single ...
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