CN115984118B - Infrared image amplification algorithm and device based on edge enhancement - Google Patents
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Abstract
An infrared image magnification algorithm based on edge enhancement, comprising: acquiring display parameters of a terminal display unit and determining basic data of an amplified image; carrying out image normalization pretreatment on an input original image to obtain a normalized image; performing edge detection on the normalized image, and dividing the normalized image into a base layer image and a detail layer image; acquiring a set of edge position pixel points when performing edge detection on the normalized image; generating an edge vector image according to the first closed graph condition formed by the pixel points in the edge position pixel point set; amplifying the detail layer image, the base layer image and the edge vector image to obtain an amplified detail image, an amplified base image and an amplified vector image, and fusing the amplified detail image and the amplified base image to obtain an amplified image; according to the positions of points of the composition lines in the amplified vector image, enabling the amplified image to present a second closed graph; and enhancing the amplified image to obtain a target image and displaying the target image on the terminal display unit.
Description
Technical Field
The invention relates to the technical field of infrared image imaging, in particular to an infrared image amplification algorithm and device based on edge enhancement.
Background
Along with the continuous expansion of the application range of the infrared image, the diversification of high-end display terminal equipment and the continuous improvement of the display resolution are realized, so that the research of an image amplification algorithm is particularly important for solving the problems of large-screen display or full-screen playing of the infrared image, and the edge of the image contains most of information of the image, which is an important part affecting the processing effect in the image amplification process and is also an object for important protection in the amplification process.
However, the existing image amplification technology cannot adaptively adjust the amplification of the infrared image according to different playing terminals, so that a rapid and efficient infrared image amplification effect is achieved.
Accordingly, the problems of the prior art are to be further improved and developed.
Disclosure of Invention
(one) object of the invention: in order to solve the problems in the prior art, the invention aims to provide an infrared image amplification algorithm and device based on edge enhancement, which have good anti-aliasing effect while protecting edge details.
(II) technical scheme: in order to solve the technical problems, the technical proposal provides an infrared image amplification algorithm based on edge enhancement, which is used for amplifying and enhancing images and comprises the following steps,
step one, acquiring display parameters of a terminal display unit, and determining basic data of an amplified image according to the display parameters;
performing image normalization pretreatment on an input original image to obtain a normalized image; performing edge detection on the normalized image, and dividing the normalized image into a base layer image and a detail layer image; the edge detection of the normalized image comprises the steps of obtaining a set of edge position pixel points; generating an edge vector image according to the first closed graph condition formed by the pixel points in the edge position pixel point set;
amplifying the detail layer image, the base layer image and the edge vector image according to the basic data of the amplified image to obtain an amplified detail image, an amplified base image and an amplified vector image; fusing the amplified detail image and the amplified basic image to obtain an amplified image;
step four, according to the positions of points forming lines in the amplified vector image, obtaining a pixel point set corresponding to the first closed figure in the amplified image, wherein the pixel point set enables the amplified image to present a second closed figure;
and fifthly, enhancing the amplified image according to the average value of the pixel point set of the second closed graph to obtain a target image.
In the second step, edge detection is performed on the normalized image by using adaptive bilateral filtering.
The infrared image amplification algorithm based on edge enhancement, wherein a first closed graph formed by the edge position pixel point set in the second step means that: in a closed graph area formed by pixel points at edge positions in a normalized image, each pixel point RGB value is different from the average value of the pixel point RGB values in the current area to obtain a first difference value, and the absolute value of the first difference value is smaller than the graph formed by the edge lines of the image formed by the pixel points with the absolute value smaller than a first threshold value.
The generating the edge vector image according to the pixel point set in the second step specifically includes that the pixel points at each edge position form a first closed figure, and an average value of RGB values of the pixel points on each first closed figure is calculated: the first average value is subjected to difference with the RGB value of each pixel point in the current first closed graph, and the absolute value is taken: the first absolute value, when the first absolute value of each first closed graph is smaller than a first threshold value, the generated edge vector image is correct; when any first absolute value in any first closed graph is larger than a first threshold, the generated edge vector image is wrong, and the first closed graph is re-planned by the pixel points forming the first closed graph, so that the first closed graph is re-planned into two or more new first closed graphs, and then the edge vector image is generated.
The infrared image amplifying algorithm based on edge enhancement, wherein in the third step, amplifying the detail layer image specifically includes: performing progressive S-type enhancement on the edge part of the detail layer image, and performing adaptive image interpolation filling on the enhanced detail layer image to obtain an amplified detail image; the amplifying of the base layer image specifically includes: and carrying out smoothing treatment on the base layer image, and carrying out bicubic interpolation filling on the base layer image after the smoothing treatment to obtain an enlarged base image.
The infrared image amplification algorithm based on edge enhancement, wherein in the third step, a weighted smooth fusion process is adopted, and the amplified detail image and the amplified base image are fused to obtain an amplified image.
The infrared image amplifying algorithm based on edge enhancement, wherein in the fifth step, according to an average value of a set of pixel points in the amplified image, which constitute a second closed figure: and the second average value is positioned in the position of the third value area to enhance the amplified image.
The infrared image amplification algorithm based on edge enhancement, wherein the third value range comprises a plurality of value ranges, and each value range corresponds to a different enhancement scheme.
The infrared image amplification algorithm based on edge enhancement, wherein the fifth step further comprises displaying the target image on the terminal display unit.
The infrared image amplifying device based on edge enhancement is used for amplifying and enhancing an image and comprises a display data acquisition unit, an image preprocessing unit, an image amplifying unit and an image enhancing unit;
the data acquisition unit acquires display parameters of the terminal display unit, and determines basic data of the amplified image according to the display parameters;
the image preprocessing unit performs image normalization preprocessing on an input original image to obtain a normalized image; the image amplifying unit performs edge detection on the normalized image and divides the normalized image into a base layer image and a detail layer image; the image amplifying unit performs edge detection on the normalized image and comprises the steps of acquiring a set of edge position pixel points; generating an edge vector image according to the first closed graph condition formed by the pixel points in the edge position pixel point set;
the image amplifying unit amplifies the detail layer image, the base layer image and the edge vector image according to the basic data of the amplified image acquired by the data acquiring unit to acquire an amplified detail image, an amplified base image and an amplified vector image, and fuses the amplified detail image and the amplified base image to acquire an amplified image;
the image enhancement unit obtains a pixel point set of a corresponding normalized image in the amplified image according to the positions of points of the component lines in the amplified vector image, and the pixel point set enables the amplified image to present a second closed graph;
and the image enhancement unit enhances the amplified image according to the average value of the pixel point set of the second closed graph to obtain a target image.
(III) beneficial effects: the infrared image amplification algorithm and the device based on edge enhancement provided by the invention have a good anti-aliasing effect, edge details are protected, meanwhile, the amplified image is subjected to block enhancement, the amplified image is clearer on the premise of ensuring that the image is not distorted, and the visual effect of the image is greatly improved.
Drawings
FIG. 1 is a schematic diagram of the steps of an infrared image magnification algorithm based on edge enhancement of the present invention;
FIG. 2 is a schematic diagram of a gray scale image adaptive contrast enhancement device according to the present invention;
FIG. 3 is an original image of an infrared image magnification algorithm in accordance with the present invention;
FIG. 4 is an enlarged image of the invention after being enlarged by the infrared image enlargement algorithm;
fig. 5 is an enlarged image obtained by enlarging only the original image by using the bicubic interpolation algorithm.
Detailed Description
The present invention will be described in further detail with reference to the preferred embodiments, and more details are set forth in the following description in order to provide a thorough understanding of the present invention, but it will be apparent that the present invention can be embodied in many other forms than described herein, and that those skilled in the art may make similar generalizations and deductions depending on the actual application without departing from the spirit of the present invention, and therefore should not be construed to limit the scope of the present invention in the context of this particular embodiment.
The drawings are schematic representations of embodiments of the invention, it being noted that the drawings are by way of example only and are not drawn to scale and should not be taken as limiting the true scope of the invention.
An infrared image amplification algorithm based on edge enhancement is used for amplifying and enhancing an infrared image, and as shown in fig. 1, the method comprises the following steps:
step one, acquiring display parameters of a terminal display unit, and determining basic data of an amplified image according to the display parameters;
the display parameters include the size of the terminal display unit, the resolution of the terminal display unit, and the like.
The basic data includes the size of the image, the resolution of the image, and the like.
Step two, carrying out pretreatment of image normalization on the input original image: counting gray scale range of one frame of image) Obtaining a normalized image;
edge detection is carried out on the normalized image, and the normalized image is divided into a basic layer image and a detail layer image;
amplifying the detail layer image and the base layer image according to the basic data of the amplified image determined in the first step, so as to obtain an amplified detail image and an amplified base image; and fusing the amplified detail image and the amplified basic image to obtain an amplified image.
The zooming in of the detail layer image specifically comprises: performing progressive S-type enhancement on the edge part of the detail layer image, and performing adaptive image interpolation filling on the enhanced detail layer image to obtain an amplified detail image;
the amplifying of the base layer image specifically includes: smoothing the base layer image, and performing bicubic interpolation filling on the smoothed base layer image to obtain an amplified base image;
in the second step, the edge detection of the normalized image is preferably performed by using adaptive bilateral filtering.
The bilateral filtering (Bilateral Filters) is a nonlinear filter that can achieve edge preservation and also smooth noise reduction. The bilateral filtering not only considers the relation of pixels in space distance during sampling, but also adds the similarity relation among pixels, so that the general block of the original image can be maintained, and the edge information can be further maintained. The filter kernel formula:
（1）
wherein: （2）
（3）
bilateral filtering is derived by Gaussian filtering and multiplying a value range filtering kernel coefficient, and the purpose of introducing the value range filtering coefficient is to maintain the gradient of the edge as much as possible, so that the bilateral filtering is a compromise algorithm on smooth filtering and edge-preserving gradient, but the complexity of the algorithm is greatly improved. Therefore, the self-adaptive bilateral filtering used in the second step of the invention divides the image into a smooth area and an edge area by analyzing the structure tensor, and only smooth denoising is considered by weighting a domain-defining kernel function (Gaussian filtering) in the smooth area; firstly, considering the weight of a emphasis range filter kernel in an edge region, setting coefficients of a kernel function according to the magnitude of an edge gradient, and carrying out bilateral filter processing to extract target edge information.
In the third step, the S-type enhancement of the edge part of the detail layer image specifically comprises the following steps,
edge enhancement is performed using the following equation (4),
（4）
wherein the method comprises the steps ofIs the gray scale of each frame of image, +.>Is the gray value of the pixel point of the smooth area, < >>Is the gray value of the pixel in the detail area of the image, < >>Representing an adaptive gamma correction, which is very efficient in enhancing the brightness and contrast of the image, +.>Representing the gamma correction coefficients. />Representation->A profile function, which is mainly enhanced for blurred edges in the image, wherein +_>Representing detail layer enhancement amplitude values. The gamma correction can optionally adjust the gray value of the image under any circumstance when +.>When the brightness and contrast of the image are enhanced. When->When the value of (2) is not changed any more, the self-adaptive adjustment can not be completed, the image can be too bright, so that some detail parts are lost, and when the edge part is processed, the effect is not ideal, therefore, the invention provides the self-adaptive +_in combination with the image gradient value>And (3) performing gradient vector operation in the directions of the x axis and the y axis respectively by establishing a coordinate system, so as to calculate the contrast enhancement amplitude among all the neighborhood pixels. />The definition formula of (2) is shown as formula (5):
（5）
computing all neighborhoods of a pixel using a formulaThe values are then normalized to [0,1 ]]To further increase the enhancement amplitude of the image, an exponential factor is introduced>For->Control being exercised, i.e.)>。/>The greater the value +.>The greater the value of +.>The value takes 1.2. In the image decomposition stage, the recombination of images is realized under the environment of 0 deviation, the deviation in the enhancement process is controlled as much as possible while the uneven brightness of the recombined images is avoided, the inversion of the low-illumination images with larger amplitude is prevented, and the brightness of the recombined images is prevented from being changed>The enhancement function should be a convex function; the center point of the coordinate system is used as a symmetry point, function origin symmetry is realized, larger-amplitude oscillation is avoided, meanwhile, the integral enhancement and the same compression ratio of the image are kept, the 0 oscillation of a detail layer is ensured, and the enhancement of the image edge is realized>The enhancement function is shown as (6):
（6）
in the third step, the self-adaptive image interpolation filling of the enhanced detail layer image specifically comprises,
interpolation filling and amplification processing is carried out on the enhanced detail layer image, and a local self-adaptive image interpolation method based on covariance similarity is adopted for the edge area detail layer of the image, so that the edge area of the image is effectively maintained. The basic idea is to estimate the covariance of the high-resolution image with the covariance of the low-resolution image according to geometric duality, and adjust interpolation coefficients to interpolate each region of the image. The interpolation function is:
（7）
wherein, the liquid crystal display device comprises a liquid crystal display device,is a pixel point to be inserted; />Is a known pixel point; />Is a weight coefficient. The weighting coefficients are derived by least square method, i.e.)>Wherein->Andthe local covariance of the high-resolution image can be obtained from the local covariance of the low-resolution image according to geometric duality, so as to obtain a weight coefficient.
The invention adopts ideal interpolation function for smooth region of imageThe third-order polynomial form of the function, i.e.> （8）
In order to ensure smooth transition of the edge region and the smooth region after interpolation is completed, firstly, carrying out local self-adaptive image interpolation filling of covariance similarity on the edge region, and then carrying out the step three: and after the smooth transition of the smooth area is carried out on the base layer image, interpolation filling of the smooth area is carried out.
And thirdly, adopting one-time weighted smooth fusion processing to fuse the amplified detail image and the amplified base image to obtain an amplified image.
The second step further comprises obtaining a set of edge position pixel points when the normalized image is subjected to edge detection, and reading RGB values of each edge position pixel point; and generating an edge vector image according to the first closed graph condition formed by the pixel points in the edge position pixel point set.
The first closed graph formed by the pixel point set at the edge position refers to: in a closed graph area formed by pixel points at edge positions in a normalized image, each pixel point RGB value is different from the average value of the pixel point RGB values in the current area to obtain a first difference value, and the absolute value of the first difference value is smaller than the edge line graph of the image formed by the pixel points with the first threshold value.
The generating of the edge vector image according to the pixel point set specifically includes that the pixel points at each edge position form a first closed graph, and an average value of RGB values of the pixel points on each first closed graph is calculated: the first average value is subjected to difference with the RGB value of each pixel point in the current first closed graph, and the absolute value is taken: the first absolute value, when the first absolute value of each first closed graph is smaller than a first threshold value, the generated edge vector image is correct; when the first absolute value of any first closed figure is larger than a first threshold value, the generated edge vector image is wrong, and the first closed figure is re-planned by the pixel points forming the first closed figure, so that the first closed figure is re-planned into two or more new first closed figures, and then the edge vector image is generated.
And step three, amplifying the edge vector image according to the basic data of the amplified image to obtain an amplified vector image.
The edge-enhanced based infrared image magnification algorithm also includes,
and step four, according to the positions of points forming lines in the amplified vector image, corresponding to the pixel points in the amplification, and obtaining a pixel point set corresponding to the normalized image in the amplified image. The pixel point set enables the enlarged image to present a second closed figure corresponding to the first closed figure formed by the pixel point set at the edge position of the normalized image.
Fifthly, according to the average value of the pixel point set forming the second closed figure in the amplified image: the second average value is positioned in the position of the third value area, and the amplified image is enhanced to obtain a target image; and displaying the target image on the terminal display unit.
The third value area includes a plurality of value ranges, and each value range corresponds to a different enhancement scheme, for example:
the third value-taking area comprises a first area [0, 50 ], and when the second average value is in the first area, the RGB value of the pixel point in the second closed graph corresponds to the amplified image minus ten percent of the RGB value of the current pixel point; a second region [ 51, 100 ], when the second mean value is in the second region, the second closed graph corresponds to the RGB value of the pixel point in the magnified image minus five percent of the RGB value of the current pixel point; a third region [ 101, 150 ], when the second average value is in the third region, the RGB values of the pixels in the corresponding enlarged image of the second closed graph remain unchanged; a fourth region [ 151, 200 ], when the second mean value is in the fourth region, the second closed graph corresponds to RGB values of pixels in the enlarged image plus ten percent of RGB values of the current pixel; a fifth region [ 201, 250 ], when the second mean value is in the fifth region, the second closed graph corresponds to RGB values of pixels in the enlarged image plus one percent of RGB values of the current pixel; a sixth region [ 251, 254 ], when the second average value is in the fifth region, the second closed graph corresponds to RGB values of pixels in the enlarged image plus five percent of RGB values of the current pixels; and a seventh area (244, 255), wherein when the second average value is in the seventh area, the RGB value of the pixel point in the second closed graph corresponding to the amplified image plus the RGB value of the current pixel point is unchanged, and when the RGB value of the pixel point in the amplified image is subjected to enhancement modification, the subtracting/adding values are all integers.
Each value range in the third value area and the corresponding enhancement scheme can be preset according to the parameters of the terminal display unit or the original image, and the smaller the range defined by each value range in the third value area is, the better the smaller the range defined by each value range is.
The first threshold is a preset value, and the third value area is a preset value area.
The infrared image amplifying device based on edge enhancement is used for amplifying and enhancing an infrared image and comprises a display data acquisition unit, an image preprocessing unit, an image amplifying unit and an image enhancing unit as shown in fig. 2;
the data acquisition unit acquires display parameters of the terminal display unit, and determines basic data of the amplified image according to the display parameters;
the image preprocessing unit performs image normalization preprocessing on an input original image to obtain a normalized image;
the image amplifying unit performs edge detection on the normalized image and divides the normalized image into a base layer image and a detail layer image; the image amplifying unit further comprises acquiring a set of edge position pixel points when performing edge detection on the normalized image; generating an edge vector image according to the first closed graph condition formed by the pixel points in the edge position pixel point set;
the image amplifying unit amplifies the detail layer image, the base layer image and the edge vector image according to the basic data of the amplified image acquired by the data acquiring unit to acquire an amplified detail image, an amplified base image and an amplified vector image, and fuses the amplified detail image and the amplified base image to acquire an amplified image;
the image enhancement unit obtains a pixel point set of a corresponding normalized image in the amplified image according to the positions of points of the component lines in the amplified vector image, and the pixel point set enables the amplified image to present a second closed graph;
the image enhancement unit enhances the amplified image according to the average value of the pixel point set of the second closed graph to obtain a target image;
the infrared image amplifying device based on edge enhancement further comprises a display output unit, wherein the display output unit displays the target image on the terminal display unit.
The infrared image amplifying algorithm and device based on edge enhancement can also amplify and enhance visible light, and are not particularly limited herein.
The infrared image amplification algorithm and the device based on edge enhancement enable edge detail information to be better protected in the image amplification process through edge detection and edge enhancement, the obtained amplified image is further enhanced, and the shooting target is displayed/restored more clearly on the premise that the target image is consistent with the shooting target.
The foregoing is a description of a preferred embodiment of the invention to assist those skilled in the art in more fully understanding the invention. However, these examples are merely illustrative, and the present invention is not to be construed as being limited to the descriptions of these examples. It should be understood that, to those skilled in the art to which the present invention pertains, several simple deductions and changes can be made without departing from the inventive concept, and these should be considered as falling within the scope of the present invention.
Claims (7)
1. An infrared image amplification algorithm based on edge enhancement, which is used for amplifying and enhancing an image, and is characterized by comprising the following steps:
step one, acquiring display parameters of a terminal display unit, and determining basic data of an amplified image according to the display parameters;
performing image normalization pretreatment on an input original image to obtain a normalized image; performing edge detection on the normalized image by using self-adaptive bilateral filtering, and dividing the normalized image into a base layer image and a detail layer image; the edge detection of the normalized image comprises the following steps: acquiring a set of edge position pixel points; generating an edge vector image according to a first closed graph condition formed by pixel points in the edge position pixel point set; the first closed figure is a closed figure formed by edge position pixel points in the normalized image; the generating an edge vector image according to the first closed graph condition formed by the pixel points in the edge position pixel point set specifically comprises: calculating an average value of RGB values of pixel points on a first closed graph as a first average value, wherein the first average value corresponds to the first closed graph, in which the absolute value of RGB value difference of each pixel point in the first closed graph is smaller than a first threshold value, as an edge vector image;
amplifying the detail layer image, the base layer image and the edge vector image according to the basic data of the amplified image to obtain an amplified detail image, an amplified base image and an amplified vector image; the zooming in of the detail layer image specifically comprises: s-type enhancement is carried out on the edge part of the detail layer image, and after self-adaptive image interpolation filling is carried out on the enhanced detail layer image, an amplified detail image is obtained; the amplifying of the base layer image specifically includes: smoothing the base layer image, and performing bicubic interpolation filling on the smoothed base layer image to obtain an amplified base image;
adopting weighted smooth fusion processing to fuse the amplified detail image and the amplified base image to obtain an amplified image;
step four, according to the positions of points forming lines in the amplified vector image, obtaining a pixel point set corresponding to the first closed figure in the amplified image, wherein the pixel point set enables the amplified image to present a second closed figure;
and fifthly, taking the average value of the pixel point set of the second closed graph as a second average value, and enhancing the amplified image according to the second average value and the position of a third value area where the second average value is located to obtain a target image.
2. The infrared image magnification algorithm based on edge enhancement according to claim 1, wherein the first closed figure formed by the set of edge position pixels in the second step is: in a closed graph area formed by pixel points at edge positions in a normalized image, each pixel point RGB value is different from the average value of the pixel point RGB values in the current area to obtain a first difference value, and the absolute value of the first difference value is smaller than the graph formed by the edge lines of the image formed by the pixel points with the absolute value smaller than a first threshold value.
3. The infrared image amplifying algorithm based on edge enhancement according to claim 2, wherein the generating the edge vector image according to the pixel point set in the second step specifically includes forming a first closed graph by the pixel points of each edge position, calculating a first average value of the pixel points on each first closed graph, and taking an absolute value of the difference between the first average value and the RGB value of each pixel point in the current first closed graph: the first absolute value, when the first absolute value of each first closed graph is smaller than a first threshold value, the generated edge vector image is correct; when any first absolute value in any first closed graph is larger than a first threshold, the generated edge vector image is wrong, and the first closed graph is re-planned by the pixel points forming the first closed graph, so that the first closed graph is re-planned into two or more new first closed graphs, and then the edge vector image is generated.
4. The infrared image magnification algorithm based on edge enhancement according to claim 1, wherein in the third step,
s-enhancement of the edge portion of the detail layer image specifically includes,
edge enhancement is performed using the following equation (4),
I out ＝I s (g/I s ) γ +S(e,d) (4)
wherein I is s Is the gray scale range of each frame of image, g is the gray scale value of the pixel point of the smooth area, d is the gray scale value of the pixel point of the detail area of the image, I s (g/I s ) γ Representing adaptive gamma correction, gamma representing gamma correction coefficients, S (e, d) representing an S-type enhancement function, e representing detail layer enhancement amplitude values;
the definition formula of gamma is shown as formula (5):
the enhancement S-type enhancement function for the image edge is realized as shown in the formula (6):
5. the edge-enhanced infrared image magnification algorithm of claim 1, wherein the third region of values comprises a plurality of ranges of values, each range of values corresponding to a different enhancement scheme.
6. The edge-enhanced based infrared image magnification algorithm of claim 1, wherein the fifth step further comprises displaying the target image on the terminal display unit.
7. An infrared image amplifying device based on edge enhancement, which is used for amplifying and enhancing an image, is characterized by comprising a display data acquisition unit, an image preprocessing unit, an image amplifying unit and an image enhancing unit:
the display data acquisition unit acquires display parameters of a terminal display unit, and determines basic data of an amplified image according to the display parameters;
the image preprocessing unit performs image normalization preprocessing on an input original image to obtain a normalized image; the image amplifying unit performs edge detection on the normalized image by using self-adaptive bilateral filtering, and divides the normalized image into a base layer image and a detail layer image; the image amplifying unit performs edge detection on the normalized image, and comprises: acquiring a set of edge position pixel points; generating an edge vector image according to a first closed graph condition formed by pixel points in the edge position pixel point set; the first closed figure is a closed figure formed by edge position pixel points in the normalized image; the generating an edge vector image according to the first closed graph condition formed by the pixel points in the edge position pixel point set specifically comprises: calculating an average value of RGB values of pixel points on a first closed graph as a first average value, wherein the first average value corresponds to the first closed graph, in which the absolute value of RGB value difference of each pixel point in the first closed graph is smaller than a first threshold value, as an edge vector image;
the image amplifying unit amplifies the detail layer image, the base layer image and the edge vector image according to the basic data of the amplified image acquired by the display data acquiring unit to acquire an amplified detail image, an amplified base image and an amplified vector image, and the amplifying of the detail layer image specifically comprises the following steps: s-type enhancement is carried out on the edge part of the detail layer image, and after self-adaptive image interpolation filling is carried out on the enhanced detail layer image, an amplified detail image is obtained; the amplifying of the base layer image specifically includes: smoothing the base layer image, and performing bicubic interpolation filling on the smoothed base layer image to obtain an amplified base image; the detail image and the basic image are fused by adopting weighted smooth fusion processing to obtain an amplified image;
the image enhancement unit obtains a pixel point set of a corresponding normalized image in the amplified image according to the positions of points of the component lines in the amplified vector image, and the pixel point set enables the amplified image to present a second closed graph;
and the image enhancement unit takes the average value of the pixel point set of the second closed graph as a second average value, and enhances the amplified image according to the second average value and the position of a third value area where the second average value is positioned to obtain a target image.
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