CN111815732A - Method for coloring intermediate infrared image - Google Patents
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Abstract
The invention discloses a method for coloring a mid-infrared image. Firstly, constructing a dictionary matched with a color image and a mid-infrared image; according to the obtained dictionary and the n neighbor principle, finding out color image small blocks matched with the small blocks of the intermediate infrared image to be colored, and further constructing a color image to obtain the intermediate infrared image after preliminary coloring; and finally, denoising the preliminarily colored intermediate infrared image by using a total variation model to obtain a final result. The method well distinguishes main objects in the image scene from the background, and the coloring effect is natural.
Description
Technical Field
The invention belongs to the field of image processing, and particularly relates to an image coloring method.
Background
With the wide application of infrared imaging technology in the military field, various image processing technologies for infrared images are rapidly developed. The coloring of the infrared image belongs to the technology which is developed in recent years, and has important significance for infrared image segmentation, target identification and the like. Infrared image imaging mainly depends on the thermal radiation of an object, and can be roughly divided into near-infrared images, intermediate-infrared images and far-infrared images according to different radiation wavelengths, and the infrared image imaging processes and the used equipment of different wave bands are different. For near-infrared images, a visible light color image and a corresponding near-infrared image can be acquired by adding an optical filter to the same lens, the color image and the near-infrared image are in a pixel-level corresponding relation, and conversion between the color image and the near-infrared image can be realized by constructing a point-to-point mapping relation. For the middle infrared image and the far infrared image, only a thermal infrared imager can be used for imaging, and the imaged image and the visible light color image have no one-to-one relation of pixel level. In the prior art, the coloring of mid-infrared images is mainly realized by using a neural network, and from the effect after coloring, objects in a scene cannot be well colored, so that the main objects in the images cannot be effectively distinguished from the background, and a pseudo coloring phenomenon exists, namely, the color of the processed objects is greatly different from the possible color of the objects in the real situation, and the difference of the colors on senses of people is very large.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a method for coloring a mid-infrared image. Firstly, constructing a dictionary matched with the intermediate infrared image and the color image; according to the obtained dictionary and the n neighbor principle, finding out color image small blocks matched with the small blocks of the intermediate infrared image to be colored, and further constructing a color image to obtain the intermediate infrared image after preliminary coloring; and finally, denoising the preliminarily colored intermediate infrared image by using a total variation model to obtain a final result. The method well distinguishes main objects in the image scene from the background, and the coloring effect is natural.
The technical scheme adopted by the invention for solving the technical problem comprises the following steps:
step 1: establishing a mid-infrared image and color image matching dictionary;
step 1-1: selecting m color images with the same size, and acquiring a mid-infrared image corresponding to each color image, wherein the size of the acquired mid-infrared image is the same as that of the color image; the color image and the corresponding intermediate infrared image form an image pair, and m groups of image pairs are shared;
step 1-2: dividing color images in the k-th group of image pairs into R-channel images, G-channel images and B-channel images according to RGB values, wherein k is 1, …, m, and dividing each channel image into p s1×s2Sorting the p rectangular small blocks of each channel image according to the position sequence of the rectangular small blocks from left to right in the channel image from top to bottom; expanding the pixels in each rectangular small block into column vectors from left to right and from top to bottom, and generating p column vectors in total; forming a two-dimensional matrix by the p column vectors of each channel, wherein the arrangement sequence of the column vectors from left to right in the two-dimensional matrix is the same as the sequence of the p rectangular small blocks corresponding to the column vectors; the three channel images form three two-dimensional matrixes which are respectively marked asAnd
dividing the mid-infrared image in the k group of image pairs into p s1×s2Sorting the p rectangular small blocks of the intermediate infrared image according to the position sequence of the rectangular small blocks from left to right in the intermediate infrared image from top to bottom; expanding pixels in each rectangular small block of the intermediate infrared image into column vectors from left to right from top to bottom, and generating p column vectors together; and then forming a two-dimensional matrix by the p column vectors, wherein the arrangement sequence of the column vectors from left to right in the two-dimensional matrix is the same as the sequence of the p rectangular small blocks corresponding to the column vectors, and the sequence is marked as DIRk;
Definition ofAndan R channel dictionary, a G channel dictionary and a B channel dictionary of the kth group of image pairs respectively;
step 1-3: adopting the processing method in the step 1-2 to obtain an R channel dictionary, a G channel dictionary and a B channel dictionary of the m groups of image pairs; combining the R channel dictionary, the G channel dictionary and the B channel dictionary of the m groups of image pairs according to the RGB three channels respectively, and the result is as follows:
the combined results are recorded as:whereinIn the form of a general R-channel dictionary,in the form of a general G-channel dictionary,a general B channel dictionary;
and DIRAre two-dimensional matrixes and have the same size; within each channel dictionary DIRAndvectors with the same sequence number in the middle column have a corresponding relation;
step 2: coloring the intermediate infrared image;
step 2-1: dividing the mid-infrared image to be colored into a s1×s2Sorting a rectangular small blocks of the intermediate infrared image according to the position sequence of the rectangular small blocks from left to right and from top to bottom in the intermediate infrared image to be colored; expanding pixels in each rectangular small block of the mid-infrared image to be colored into column vectors from left to right and from top to bottom, and generating a column vectors; and then forming a two-dimensional matrix by the a column vectors, wherein the arrangement sequence of the column vectors from left to right in the two-dimensional matrix is the same as the sequence of the a rectangular small blocks corresponding to the column vectors, and the sequence is marked asIRWhere the ith rectangular patch generates a column vector denotedi IR;
Step 2-2: using n nearest neighbor principle in matrix DIRIs found ini IRThe nearest n column vectors are represented asUsing the total R channel dictionary, the total G channel dictionary and the total B channel dictionary to obtainIn a two-dimensional matrixAndthe corresponding n column vectors with the same column sequence number are respectivelyAnd
in the formula (I), the compound is shown in the specification,respectively representing RGB three channel image small block column vectors corresponding to column vectors generated by the ith rectangular small block of the intermediate infrared image to be colored; according to the pixel sequence when the pixels in each rectangular small block are expanded into the column vectors from left to right and from top to bottom in the step 1-2, the column vectors of the RGB three-channel image small blocks are arranged Restoring the image into small image blocks of three channels of RGB;
wjfor weight, the following is calculated:
step 2-3: processing each image small block divided by the intermediate infrared image to be colored in the step 2-2 to obtain image small blocks of three channels of RGB corresponding to each image small block of the intermediate infrared image; splicing the image small blocks of the three RGB channels corresponding to each image small block of the obtained intermediate infrared image into three complete RGB channel images respectively from left to right and from top to bottom when the intermediate infrared image is segmented according to the step 2-1, and superposing the three obtained RGB channel images into a three-dimensional matrix, thereby obtaining a color image Z after preliminary coloring;
and step 3: denoising by adopting a total variation model, and constructing an objective function:
wherein, X is a color image colored on the mid-infrared image after denoising,in order to differentiate X, lambda is a penalty factor;
and iterating once to obtain:
Preferably, the method for acquiring the mid-infrared image corresponding to each color image in step 1-1 is as follows: the method comprises the following steps of adopting an infrared camera and a visible light camera to take a picture of the same scene for sampling, and obtaining an image pair of a color image and a middle infrared image after image distortion removal, zooming and alignment;
preferably, s is as described in Steps 1-21=10,s2=10。
Preferably, n of the n neighbor principle described in step 2-2 is equal to 10.
Preferably, the n-nearest neighbor principle method described in step 2-2 is as follows:
computingi IRAnd matrix DIRThe distance between every two column vectors in the vector sum is the two norms of the vectors obtained after the subtraction of the two vectors; sorting all the distances obtained by calculation from small to large, and taking D corresponding to the first n distancesIRThe column vector of (2).
Preferably, λ ═ 0 and d ═ 0.2 in step 3.
Preferably, the differentiation method in step 3 is to replace the differential value with the difference value between the pixel and the pixel in its eight neighborhoods.
Due to the adoption of the method for coloring the mid-infrared image, the main objects in the image scene can be distinguished from the background after the mid-infrared image is colored, and the coloring effect is natural.
Drawings
FIG. 1 is a schematic diagram of a color image versus mid-infrared image;
FIG. 2 is a mid-infrared image to be colored using the method of the present invention;
FIG. 3 is a three pairs of color and mid-infrared image pairs selected for use in generating a dictionary when coloring FIG. 2;
FIG. 4 is an image of the RGB three channels rendered on FIG. 2 by the method of the present invention;
FIG. 5 is a preliminary color image resulting from the method of the present invention after coloring FIG. 2;
FIG. 6 shows the result of denoising the primary color image by the holomorphic model according to the method of the present invention;
Detailed Description
The invention is further illustrated with reference to the following figures and examples.
A method for coloring a mid-infrared image. The method comprises the following steps:
step 1: establishing a mid-infrared image and color image matching dictionary;
step 1-1: selecting m color images with the same size, and acquiring a mid-infrared image corresponding to each color image, wherein the size of the acquired mid-infrared image is the same as that of the color image; the color image and the corresponding intermediate infrared image form an image pair, and m groups of image pairs are shared;
step 1-2: dividing color images in the k-th group of image pairs into R-channel images, G-channel images and B-channel images according to RGB values, wherein k is 1, …, m, and dividing each channel image into p s1×s2Sorting the p rectangular small blocks of each channel image according to the position sequence of the rectangular small blocks from left to right in the channel image from top to bottom; expanding the pixels in each rectangular small block into column vectors from left to right and from top to bottom, and generating p column vectors in total; forming a two-dimensional matrix by the p column vectors of each channel, wherein the arrangement sequence of the column vectors from left to right in the two-dimensional matrix is the same as the sequence of the p rectangular small blocks corresponding to the column vectors; the three channel images form three two-dimensional matrixes which are respectively marked asAnd
dividing the mid-infrared image in the k group of image pairs into p s1×s2Sorting the p rectangular small blocks of the intermediate infrared image according to the position sequence of the rectangular small blocks from left to right in the intermediate infrared image from top to bottom; each rectangle of the intermediate infrared image is reducedExpanding the pixels in the block into column vectors from left to right from top to bottom, and generating p column vectors together; and then forming a two-dimensional matrix by the p column vectors, wherein the arrangement sequence of the column vectors from left to right in the two-dimensional matrix is the same as the sequence of the p rectangular small blocks corresponding to the column vectors, and the sequence is marked as DIRk;
Definition ofAndan R channel dictionary, a G channel dictionary and a B channel dictionary of the kth group of image pairs respectively;
step 1-3: adopting the processing method in the step 1-2 to obtain an R channel dictionary, a G channel dictionary and a B channel dictionary of the m groups of image pairs; combining the R channel dictionary, the G channel dictionary and the B channel dictionary of the m groups of image pairs according to the RGB three channels respectively, and the result is as follows:
the combined results are recorded as:whereinIn the form of a general R-channel dictionary,in the form of a general G-channel dictionary,a general B channel dictionary;
and DIRAre two-dimensional matrixes and have the same size; within each channel dictionary DIRAndvectors with the same sequence number in the middle column have a corresponding relation;
step 2: coloring the intermediate infrared image;
step 2-1: dividing the mid-infrared image to be colored into a s1×s2Sorting a rectangular small blocks of the intermediate infrared image according to the position sequence of the rectangular small blocks from left to right and from top to bottom in the intermediate infrared image to be colored; expanding pixels in each rectangular small block of the mid-infrared image to be colored into column vectors from left to right and from top to bottom, and generating a column vectors; and then forming a two-dimensional matrix by the a column vectors, wherein the arrangement sequence of the column vectors from left to right in the two-dimensional matrix is the same as the sequence of the a rectangular small blocks corresponding to the column vectors, and the sequence is marked asIRWhere the ith rectangular patch generates a column vector denotedi IR;
Step 2-2: using n nearest neighbor principle in matrix DIRIs found ini IRThe nearest n column vectors are represented asUsing the total R channel dictionary, the total G channel dictionary and the total B channel dictionary to obtainIn a two-dimensional matrixAndthe corresponding n column vectors with the same column sequence number are respectivelyAnd
in the formula (I), the compound is shown in the specification,respectively representing RGB three channel image small block column vectors corresponding to column vectors generated by the ith rectangular small block of the intermediate infrared image to be colored; according to the pixel sequence when the pixels in each rectangular small block are expanded into the column vectors from left to right and from top to bottom in the step 1-2, the column vectors of the RGB three-channel image small blocks are arranged Restoring the image into small image blocks of three channels of RGB;
wjfor weight, the following is calculated:
step 2-3: processing each image small block divided by the intermediate infrared image to be colored in the step 2-2 to obtain image small blocks of three channels of RGB corresponding to each image small block of the intermediate infrared image; splicing the image small blocks of the three RGB channels corresponding to each image small block of the obtained intermediate infrared image into three complete RGB channel images respectively from left to right and from top to bottom when the intermediate infrared image is segmented according to the step 2-1, and superposing the three obtained RGB channel images into a three-dimensional matrix, thereby obtaining a color image Z after preliminary coloring;
and step 3: denoising by adopting a total variation model, and constructing an objective function:
wherein, X is a color image colored on the mid-infrared image after denoising,in order to differentiate X, lambda is a penalty factor;
and iterating once to obtain:
Example (b):
the embodiment relates to a method for acquiring a color image and a corresponding intermediate infrared image, which comprises the steps of adopting an infrared camera and a visible light camera to shoot and sample the same scene, and obtaining a series of image pairs matched with the color image and the intermediate infrared image after image distortion removal, zooming and alignment. Fig. 1 shows a pair of processed images, a color image on the left and a mid-infrared image on the right, and it can be seen that the position and size of the same object in different images are approximately the same. The selected mid-infrared image to be colored is shown in fig. 2.
1. According to the mid-infrared image to be colored in fig. 2, three mid-infrared images with contents similar to those of the mid-infrared image in fig. 2 and corresponding visible light color images of the three mid-infrared images are selected, fig. 3 shows three pairs of the visible light color images and the mid-infrared images selected corresponding to fig. 2, the left side is a color image, and the right side is a mid-infrared image. Since the color image has three channels, a phase is taken in each channelAnd the same operation is carried out, and the dictionary is constructed for the three pairs of images according to the step 1Size s of the division block1×s210 x 10 was chosen. Within each dictionary DIRAndvectors with the same sequence number in the middle column have a corresponding relation, and the corresponding relation is the key for coloring the infrared image.
2. Coloring the mid-infrared image to be colored to obtain an image after preliminary coloring;
dividing the mid-infrared image to be colored into a plurality of small blocks with the size of 10 x 10, wherein the column vector generated by the ith rectangular small block is recorded asi IRAt DIRFind 10 AND's in the column vectori IRThe nearest vectors, the 10 nearest vectors are represented asUsing the global R channel dictionary, global G channel dictionary and global B channel dictionary,in a two-dimensional matrixAndcorresponding column vector isAndthese vectors are summed weighted:
The above steps are taken for each small block of the image to be colored, the obtained three-channel color image small block column vectors are converted into three-channel color image small blocks of 10 × 10 again, images of three channels of RGB are obtained through splicing, as shown in FIG. 4, and the obtained three images of the channels of RGB are superposed into a three-dimensional matrix, so that a preliminary colored image Z is obtained, as shown in FIG. 5.
3. Denoising the preliminarily colored image obtained in the last step by using the total variation model in the step 3;
taking lambda as 0 and d as 0.2, and iterating only once to obtain the denoised image shown in FIG. 6.
According to the simulation result, the invention can be used for coloring the mid-infrared image, so that the object and the background are well separated, and the coloring effect is natural.
Claims (7)
1. A method for coloring a mid-infrared image, comprising the steps of:
step 1: establishing a mid-infrared image and color image matching dictionary;
step 1-1: selecting m color images with the same size, and acquiring a mid-infrared image corresponding to each color image, wherein the size of the acquired mid-infrared image is the same as that of the color image; the color image and the corresponding intermediate infrared image form an image pair, and m groups of image pairs are shared;
step 1-2: dividing color images in the kth group of image pairs into R channel images, G channel images and B channels according to RGB valuesA channel image, k 1, …, m, each of which is divided into p s1×s2Sorting the p rectangular small blocks of each channel image according to the position sequence of the rectangular small blocks from left to right in the channel image from top to bottom; expanding the pixels in each rectangular small block into column vectors from left to right and from top to bottom, and generating p column vectors; forming a two-dimensional matrix by the p column vectors of each channel, wherein the arrangement sequence of the column vectors from left to right in the two-dimensional matrix is the same as the sequence of the p rectangular small blocks corresponding to the column vectors; the three channel images form three two-dimensional matrixes which are respectively marked asAnd
dividing the mid-infrared image in the k group of image pairs into p s1×s2Sorting the p rectangular small blocks of the intermediate infrared image according to the position sequence of the rectangular small blocks from left to right in the intermediate infrared image from top to bottom; expanding pixels in each rectangular small block of the intermediate infrared image into column vectors from left to right from top to bottom, and generating p column vectors together; and then forming a two-dimensional matrix by the p column vectors, wherein the arrangement sequence of the column vectors from left to right in the two-dimensional matrix is the same as the sequence of the p rectangular small blocks corresponding to the column vectors, and the sequence is marked as DIRk;
Definition ofAndan R channel dictionary, a G channel dictionary and a B channel dictionary of the kth group of image pairs respectively;
step 1-3: adopting the processing method in the step 1-2 to obtain an R channel dictionary, a G channel dictionary and a B channel dictionary of the m groups of image pairs; combining the R channel dictionary, the G channel dictionary and the B channel dictionary of the m groups of image pairs according to the RGB three channels respectively, and the result is as follows:
the combined results are recorded as:whereinIn the form of a general R-channel dictionary,in the form of a general G-channel dictionary,a general B channel dictionary;
and DIRAre two-dimensional matrixes and have the same size; within each channel dictionary DIRAndvectors with the same sequence number in the middle column have a corresponding relation;
step 2: coloring the intermediate infrared image;
step 2-1: dividing the mid-infrared image to be colored into a s1×s2Sorting a rectangular small blocks of the intermediate infrared image according to the position sequence of the rectangular small blocks from left to right and from top to bottom in the intermediate infrared image to be colored; expanding pixels in each rectangular small block of the mid-infrared image to be colored into column vectors from left to right and from top to bottom, and generating a column vectors; and then forming a column vectors into a two-dimensional matrix, wherein the arrangement sequence of the column vectors from left to right in the two-dimensional matrix is the same as the sequence of a rectangular small blocks corresponding to the column vectorsIs marked asIRWhere the ith rectangular patch generates a column vector denoted
Step 2-2: using n nearest neighbor principle in matrix DIRIs found inThe nearest n column vectors are represented asUsing the total R channel dictionary, the total G channel dictionary and the total B channel dictionary to obtainIn a two-dimensional matrixAndthe corresponding n column vectors with the same column sequence number are respectivelyAnd
in the formula (I), the compound is shown in the specification,respectively representing RGB three channel image small block column vectors corresponding to column vectors generated by the ith rectangular small block of the intermediate infrared image to be colored; according to the pixel sequence when the pixels in each rectangular small block are expanded into the column vectors from left to right and from top to bottom in the step 1-2, the column vectors of the RGB three-channel image small blocks are arranged Restoring the image into small image blocks of three channels of RGB;
wjfor weight, the following is calculated:
step 2-3: processing each image small block divided by the intermediate infrared image to be colored in the step 2-2 to obtain image small blocks of three channels of RGB corresponding to each image small block of the intermediate infrared image; splicing the image small blocks of the three RGB channels corresponding to each image small block of the obtained intermediate infrared image into three complete RGB channel images respectively from left to right and from top to bottom when the intermediate infrared image is segmented according to the step 2-1, and superposing the three obtained RGB channel images into a three-dimensional matrix, thereby obtaining a color image Z after preliminary coloring;
and step 3: denoising by adopting a total variation model, and constructing an objective function:
wherein, X is a color image colored on the mid-infrared image after denoising,in order to differentiate X, lambda is a penalty factor;
and iterating once to obtain:
2. A method for coloring a mid-infrared image according to claim 1, wherein the method for acquiring the mid-infrared image corresponding to each color image in step 1-1 is as follows: the method comprises the steps of adopting an infrared camera and a visible light camera to shoot and sample the same scene, and obtaining an image pair of a color image and a middle infrared image after image distortion removal, zooming and alignment.
3. A method for coloring an intermediate infrared image according to claim 1, wherein s in step 1-21=10,s2=10。
4. A method for coloring an intermediate infrared image according to claim 1, wherein n of the n-nearest neighbor principle in step 2-2 is 10.
5. A method for coloring an intermediate infrared image according to claim 1, wherein the n-nearest neighbor principle method of step 2-2 is as follows:
computingAnd matrix DIRThe distance between every two column vectors in the vector sum is the two norms of the vectors obtained after the subtraction of the two vectors; sorting all the distances obtained by calculation from small to large, and taking D corresponding to the first n distancesIRThe column vector of (2).
6. A method for coloring an intermediate infrared image according to claim 1, wherein λ is 0 and d is 0.2 in step 3.
7. A method as claimed in claim 1, wherein the differentiation method in step 3 is to replace the differentiation value with the difference between the pixel and the pixel in its eight neighborhoods.
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