Method for collecting and processing ice core optical characteristic image
A technology of image acquisition and processing and optical characteristics, applied in the field of image processing, can solve the problems that researchers cannot preserve the original information of ice cores, and achieve good results
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Embodiment 1
[0048] see figure 1 , which is a flow chart of the steps of the ice core optical characteristic image acquisition and processing method according to Embodiment 1 of the method of the present invention, including the following steps:
[0049] S10, taking multiple pictures of the ice core;
[0050] S201, image preprocessing, using a histogram equalization method to non-linearly stretch the ice core photo, and redistribute pixel values;
[0051] S202, image matching area positioning, determining overlapping areas of two adjacent photos, and extracting and registering feature points;
[0052] S203, image feature extraction, corner detection using FAST function;
[0053] S204, image feature matching, using the Euclidean distance between two feature point descriptors as a similarity criterion for feature point matching;
[0054] S205, image fusion, using weighted average fusion to perform seamless stitching after image smooth transition;
[0055] S30, performing optical analysis...
Embodiment 2
[0059] S201 Image preprocessing includes the following steps:
[0060] The first step is to count the number of pixels n of each gray level of the original input image i , i=0,1,...L-1, where L is the total number of gray levels;
[0061] Step 2: Calculate the original image histogram, that is, the probability density Pi of each gray level, obtained according to the following formula,
[0062]
[0063] Among them, n is the total number of pixels of the original image, r i is the gray level i;
[0064] Step 3: Calculate the cumulative distribution function s k , obtained according to the following formula,
[0065]
[0066] Step 4: Calculate the final output gray level gk, obtained according to the following formula,
[0067] g k =INT[(L-1)s k (r k )+0.5] / (L-1),
[0068] Among them, INT[] is the integer operator.
[0069] Due to the high light transmittance of ice cores, the photos taken are generally brighter. Therefore, the gray value of the original image of...
Embodiment 3
[0071] S203 image feature extraction comprises the following steps:
[0072] Step 1: Take a pixel p as the center and select 16 pixel points on a circle with a radius of 3, and make a difference with the pixel value of the center point, and obtain the number satisfying the inequality according to the following formula,
[0073]
[0074] Among them, I(x) is the pixel value of the pixel point on the side, I(p) is the pixel value of the center point, ε d is the set threshold, and N is the number satisfying the inequality;
[0075] Step 2: If N>12, then this point is used as a candidate corner point, otherwise, delete it;
[0076] Step 3: Perform non-maximum value suppression on the image. If there are multiple feature points in a neighborhood centered on feature point p, judge the score of each feature point. If p is the highest score of all feature points in the neighborhood , then keep it; otherwise, delete it; if there is only one feature point in the neighborhood, keep i...
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