CN112132749A - Image processing method and device applying parameterized Thiele continuous fractional interpolation - Google Patents
Image processing method and device applying parameterized Thiele continuous fractional interpolation Download PDFInfo
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Abstract
The invention discloses an image processing method and device applying parameterized Thiele continuous fractional interpolation, comprising the following steps: converting an image to be processed into a color space and extracting a corresponding channel image; carrying out frequency domain space conversion on different channels, and adopting a matched filtering method based on the characteristics of the different channels to suppress low-frequency components in a channel frequency spectrum and improve corresponding channel components; based on different channels with increased components, filtering smooth areas and non-smooth areas of channel images to different degrees through a filter, and carrying out a denoising process based on edge protection; based on different channel images, carrying out image super-resolution reconstruction by a parameterized Thiele continuous fractional interpolation method to obtain a high-resolution image; the invention realizes the image enhancement of the subareas, avoids the image edge blurring, simultaneously realizes the interpolation of the subareas and simultaneously realizes the debugging and correction in the subareas to achieve the optimal interpolation reconstruction effect.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to an image processing method and device applying parameterized Thiele continuous fractional interpolation.
Background
In the process of obtaining the image, the image may be affected by factors such as the intensity of ambient light in the dynamic range of the imaging device, which may cause the image to have the phenomena of low contrast, unobvious image information, color distortion, insufficient definition of the outline or boundary information of the target, etc., thereby bringing difficulties to human visual observation and machine analysis processing, and thus the image needs to be enhanced. Image enhancement refers to a processing method for highlighting some information of an image according to specific needs and weakening or removing some unnecessary information, and is the most basic means of image processing, and is often a preprocessing process in various image analysis and processing.
More than ninety percent of information acquired by human beings comes from vision, and natural and real scenes are colorful, so that the information contained in the color images is far more than that of other types of images, but the processing difficulty of the colorful images is far more than that of other types of images because various problems are still to be solved in the process of the colorful images. At present, the content of documents and books related to image processing is more than 90% of gray level image processing. Meanwhile, the currently common image enhancement methods can be mainly divided into sharpening enhancement, fuzzy set enhancement, multi-scale geometric enhancement, enhancement methods based on differential operators and the like. Aiming at different image imaging characteristics, various methods have advantages and disadvantages, for example, sharpening enhancement can enhance small details and edge parts of an image, but multi-scale geometric enhancement which is sensitive to noise can be realized, and multiple scales can perform targeted enhancement on the image, but a ringing effect is easily generated; the reinforcement based on the differential operator can effectively process structures such as angular points, tubular structures and the like, but can not well solve the problem of the grammatical details in the smooth region in the detected image, so that the image quality is not high.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an image processing method applying parameterized Thiele continuous fractional interpolation, which is used for carrying out regional image enhancement, noise reduction and interpolation reconstruction on a color image, thereby realizing high quality and high definition of the image after image processing.
The invention relates to an image processing method applying parameterized Thiele continuous fractional interpolation, which comprises the following steps of:
converting an image to be processed into a color space and extracting a corresponding channel image, wherein the channel image at least comprises a channel representing the brightness of the image;
carrying out frequency domain space conversion on different channels, and adopting a matched filtering method based on the characteristics of the different channels to suppress low-frequency components in a channel frequency spectrum and improve corresponding channel components;
based on different channels with increased components, filtering smooth areas and non-smooth areas of channel images to different degrees through a filter, and carrying out a denoising process based on edge protection;
based on different channel images, carrying out image super-resolution reconstruction by a parameterized Thiele continuous fractional interpolation method to obtain a high-resolution image;
and performing color space inverse conversion to restore the original color space, and obtaining a high-resolution and high-quality image.
As a further optimization of the scheme, the formula of the parameterized Thiele continuous fractional interpolation adopts binary Thiele continuous fractional interpolation containing single parameter.
As a further optimization of the above scheme, the binary Thiele-containing continuous fraction interpolation with single parameter is:
wherein the content of the first and second substances,
j is 0,1,. and n; 1,2,. m; i ═ p, p + 1.., m,
ak,0,ak,1,...,ak,l,
ak,l+1,ak,l+2,...,ak,nin the formula
The calculated value after introducing the parameter lambda.
P is 0, 1., k-1, k +1,.., m; q ═ 1,2,. n; j ═ q, q + 1.., n,
as a further optimization of the above scheme, the image super-resolution reconstruction is performed by using a parameterized Thiele continuous fractional interpolation method to obtain a high-resolution image, different regions are divided based on image gradient changes, interpolation is performed by using parameterized Thiele continuous fractional interpolation formulas respectively, and the interpolation formula of each region optimizes the interpolation image based on the adjustment of variable parameters.
As a further optimization of the above scheme, the performing super-resolution image reconstruction by using a parameterized Thiele continuous fractional interpolation method to obtain a high-resolution image further includes:
performing image quality calculation on an image obtained by image super-resolution reconstruction based on a preset evaluation index;
if the image quality data does not meet the preset high-resolution image condition, iteration of the image super-resolution reconstruction process is carried out by changing the variable parameters in the parameterized Thiele continuous fractional interpolation until an image meeting the preset high-resolution image condition is obtained.
As a further optimization of the above scheme, the image to be processed is converted into a color space and a corresponding channel image is extracted, specifically, the image is converted from RGB into HSV color space.
As a further optimization of the above scheme, the performing frequency-domain spatial conversion on different channels, and adopting a matched filtering method based on the characteristics of different channels to suppress low-frequency components in a channel spectrum and improve corresponding channel components includes:
sliding the S-channel image and the V-channel image based on a preset sliding window, and performing homomorphic filtering on an image area in each sliding window, wherein the homomorphic filtering cut-off frequency of each image area is matched with the frequency spectrum of the image area;
and merging the homomorphically filtered images of all the sliding window image areas to obtain an S-channel image with enhanced saturation and a V-channel image with enhanced brightness contrast.
As a further optimization of the above scheme, the filtering, by a filter, the smoothing region and the non-smoothing region of the channel image to different degrees, and performing the denoising process based on the edge protection includes:
filtering based on a filter model, wherein the model is as follows:
parameter a of the modelp′,bp′Satisfying the objective optimization function E:
wherein G is a guide map, X is an image before filtering, G and X are allowed to be the same,
is a window with p' as the center and ζ 1 as the radius,
is a filtered image, ap′And bp′Is that
Two constants in the window are set to be constant,
is the edge perceptual weight, which is the local variance ratio of all pixels of a 3x3 window pixel and (2 ζ 1+1) x (2 ζ 1+1) window, χ (p') ═ σG,1(p′)σG,ζ1(p′)，σG,1(p') and σG,ζ1(p') respectively show the image G in the window omega1(p') and
standard deviation of (0.001 x L)2L is the dynamic range of image X; k is a constant; var (x (p) -x (p ') represents the difference between the variance of x (p) and x (p'); var (x (p) -min (x (p)) represents the difference between the variance of x (p) and the minimum value of x (p).
The invention provides an image processing device applying parameterized Thiele continuous fractional interpolation, which comprises:
the image channel image extraction unit is used for converting the image to be processed into a color space and extracting a corresponding channel image, wherein the channel image at least comprises a channel representing the image brightness;
the channel image enhancement unit is used for carrying out frequency domain space conversion on different channels, and adopting a matched filtering method based on the characteristics of the different channels to inhibit low-frequency components in a channel frequency spectrum and improve corresponding channel components;
the noise reduction and edge protection unit is used for filtering smooth areas and non-smooth areas of channel images to different degrees through a filter based on different channels with improved components and carrying out a noise reduction process based on edge protection;
the high-resolution channel image acquisition unit is used for carrying out image super-resolution reconstruction by a parameterized Thiele continuous fractional interpolation method based on different channel images to acquire a high-resolution image;
and the channel image fusion unit is used for carrying out color space inverse conversion and recovering to the original color space to obtain a high-resolution and high-quality image.
Based on the image processing method using parameterized Thiele continuous fractional interpolation, the invention also provides electronic equipment, which is characterized by comprising the following steps:
a memory for storing executable instructions;
a processor for implementing the image processing method applying parameterized Thiele continuous fraction interpolation of any one of claims 1 to 8 when executing the executable instructions stored in the memory.
The image processing method applying the parameterized Thiele continuous fractional interpolation has the following beneficial effects:
1. according to the method, the images of the channels in the HSV channel are respectively enhanced, so that brightness enhancement and saturation enhancement are realized, the quality of the processed images is improved, meanwhile, sliding is performed based on the preset sliding window in the enhancement process, homomorphic filtering is performed on the image area in each sliding window, the homomorphic filtering cutoff frequency of each image area is matched with the frequency spectrum of the image area, the unreasonable brightness improvement of the bright area caused by the fact that the same filter parameters are adopted to perform equal brightness improvement on the dark area and the bright area in the original image, and the brightness of the image after the brightness improvement is uniform.
2. In the process of denoising after image enhancement, the invention carries out the denoising process based on edge protection by filtering the smooth region and the non-smooth region of the channel image to different degrees, thereby realizing the protection of the edge region and the texture region of the image while denoising, and avoiding the blurring of the non-smooth regions caused by the denoising of the filter.
3. In the process of image interpolation reconstruction, binary Thiele continuous fractional interpolation containing single parameter is adopted, and based on the characteristic that the constructed interpolation function can realize various interpolation effects based on various values of variable parameters, different interpolation of subareas is realized, and the optimal interpolation reconstruction effect of interpolation debugging and correction in the subareas is realized.
Drawings
FIG. 1 is a block diagram of the overall flow of the image processing method of the present invention using parameterized Thiele fractional interpolation;
FIG. 2 is a block diagram of a flow chart of a method for enhancing channel components by filtering for each channel image in FIG. 1;
FIG. 3 is a block diagram of a flow chart of a method for obtaining a high resolution image by interpolation for each channel image in FIG. 1;
fig. 4 is a block diagram showing the configuration of an image processing apparatus using parameterized Thiele continuous fractional interpolation according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail with reference to the accompanying drawings, the described embodiments should not be construed as limiting the present invention, and all other embodiments obtained by a person of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.
For low-quality images which are frequently encountered in life, due to the fact that the brightness of the images is weak due to poor illumination intensity when the images are collected, most contents in the images are difficult to recognize, important contents in the images cannot be obtained, and the identification and content extraction of the image contents are influenced.
The image processing method applying the parameterized Thiele continuous fractional interpolation comprises the following steps of:
converting an image to be processed into a color space and extracting a corresponding channel image, wherein the channel image at least comprises a channel representing the brightness of the image; in the embodiment, specifically, the image is converted from RGB to HSV color space, and H channel, S channel and V channel images therein are extracted; respectively processing the three channel images and then converting the color space to restore the original color space, namely an RGB color space;
carrying out frequency domain space conversion on different channels, and adopting a matched filtering method based on the characteristics of the different channels to suppress low-frequency components in a channel frequency spectrum and improve corresponding channel components;
specifically, considering that the purpose is to improve the brightness contrast and the image saturation of an image, sliding the S-channel and V-channel images based on a preset sliding window, and performing homomorphic filtering on an image region in each sliding window, where the homomorphic filtering cutoff frequency of each image region matches the image region spectrum; the method comprises the steps that an image is divided into a plurality of areas in a sliding mode through a preset sliding window in the homomorphic filtering process, homomorphic filters are used for filtering respectively, the cut-off frequency of each filter is set based on different areas, the condition that the brightness of the bright areas is unreasonably improved due to the fact that the brightness of the dark areas and the brightness of the bright areas in the original image is improved to the same degree due to the fact that the same filter parameters are used for filtering all the areas can be avoided, the brightness of the bright areas is improved unreasonably, the brightness of the image after the brightness is improved is uniform, meanwhile, the whole area is divided through the sliding window, the original size of the image is not limited, and;
merging the homomorphically filtered images of all the sliding window image areas to obtain an S-channel image with enhanced saturation and a V-channel image with enhanced brightness contrast;
in order to remove noise brought by the image enhancement process, based on different channels with improved components, filtering smooth regions and non-smooth regions of channel images to different degrees through a filter, and carrying out a denoising process based on edge protection;
specifically, filtering is performed based on a filter model, where the model is:
wherein the content of the first and second substances,
is a filtered image, G is a directed graph, and the model is
And G has a local linear relationship in the window centered on the pixel p ', when the guide image has an edge, the output image has an edge, specifically if the pixel p' is at the edge, ap′Is 1, if the pixel p' is in a flat area, then ap′Is 0 so that the smooth region becomes smooth.
To solve the parameter ap′,bp′Setting X as an image before filtering to
The minimum difference between X and X is the target, the linear parameter a of the modelp′,bp′Satisfying the objective optimization function E:
wherein G in the guide map is the guide map, X is the image before filtering, G and X are allowed to be the same, G and X are the same in the embodiment, the protection of the edge information in the filtering process is realized,
a window centered at p', zeta 1 being the radius,
is a filtered image, ap′And bp′Is that
Two constants in the window are set to be constant,
is the edge perceptual weight, which is the local variance ratio of all pixels of a 3x3 window pixel and (2 ζ 1+1) x (2 ζ 1+1) window, χ (p') ═ σG,1(p′)σG,ζ1(p′)，σG,1(p') and σG,ζ1(p') respectively show the image G in the window omega1(p') and
the standard deviation of (a) is a very small constant having a value of (0.001X L)2L is the dynamic range of image X; k is a constant, typically a value of 4; var (x (p) -x (p ') represents the difference between the variance of x (p) and x (p'); var (x (p) -min (x (p)) represents the difference between the variance of x (p) and the minimum value of x (p).
Parameters in the objective optimization function E in the filter modelp′The size of the filter model is related to the difference value of the variance of the pixels in the region and all the pixels, so that the filtering effect of the whole filter model is related to the difference value of the variance of the pixels in the window region and all the pixels in the image, different filtering and noise reduction processes are realized for the smooth region and the non-smooth region (edge or texture region), and the non-smooth region of the image after noise reduction processing is effectively prevented from being blurred.
Based on different channel images, carrying out image super-resolution reconstruction by a parameterized Thiele continuous fractional interpolation method to obtain a high-resolution image; specifically, the formula of the parameterized Thiele continuous fractional interpolation adopts binary Thiele continuous fractional interpolation containing single parameter, and the method for constructing the binary Thiele continuous fractional interpolation containing single parameter is as follows:
for a given two-dimensional set of points of dissimilarity Πm,n{(xi,yj) I ═ 0,1, K, m; j is 0,1, K, n, assuming that
And f (x, y) is a real function defined on D, and
f(xi,yj)＝fi,j,i＝0,1,K,m；j＝0,1,K,n, (1)
easily construct binary Thiele continuous fraction interpolation:
wherein i is 0,1, …, m; j is 0,1, …, n,
and the denominator term in the formula is a binary contrast quotient.
Introducing a parameter lambda into the formula, and constructing binary Thiele continuous fractional interpolation containing a single parameter, wherein the method specifically comprises the following steps:
step 1: initialization, order
Step 2: for j ═ 0,1, …, n; p is 1,2, …, m; i ═ p, p +1, …, m,
order to
Step 3: p is 0,1, …, k-1, k +1, …, m; q is 1,2, …, n; j is q, q +1, …, n,
order to
Step 4: in the pair (4) formula
Introducing a parameter lambda, calculated according to the formulae (4-1) to (4-4):
to pair
When j is 1, …, k +1, pair q is j, j +1, …, n;
the sum of the values of j ═ k +1, k +2, …, n,
when j is k +2, k +3, …, n, pair q is j, j +1, …, n; ,
obtained by the above calculation
The coefficients are collectively noted as:
step 5: constructing a single parameter unitary Thiele continuous fraction interpolation about y by using the elements in the formula (5) and the elements in the formula (6):
step 6: order to
Then
I.e. a binary Thiele continuous fraction interpolation function containing single parameter on a given point set, A1(y)，A2(y)，...，Am(y) is the binary contrast quotient of the interpolation function.
The continued fraction interpolation function constructed by the algorithm can be proved to meet the theorem:
and (3) proving that: for any node (x)i,yj,fi,j) When i is 0,1, …, k-1, k +1, …, m,
is easy to see
When the value of i is equal to k,
j is more than or equal to 0 and less than l, l is j, n is more than or equal to j and more than l
As is readily known from the theorem 4,
Theorem 4 order
Is a different rectangular grid on the rectangular domain D, and f (x, y) is a real function defined on the rectangular domain D, then the binary parametric Thiele continuous fraction interpolation satisfies
In the process of interpolation processing based on the continuous fractional interpolation, different areas are divided based on image gradient change, pixel areas of a gradual gradient change area and a non-gradual gradient change area are respectively interpolated by adopting a parameterized Thiele continuous fractional interpolation formula, and the interpolation formula of each area optimizes an interpolation image based on the adjustment of variable parameters. And different interpolation effects in different areas are realized, so that the pixel value of the interpolation point is more consistent with the real pixel value, and a better interpolation effect is realized.
In addition, based on the interpolation formula provided in the embodiment of the present invention, different interpolation effects can be achieved by adjusting through alignment based on the variable parameter λ in the interpolation formula, so that in the embodiment of the present invention, if interpolation data of a point to be interpolated does not meet a requirement, iterative correction can be performed until an image with optimal interpolation reconstruction is obtained, specifically, image super-resolution reconstruction is performed through a parameterized Thiele continuous fraction interpolation method to obtain a high-resolution image, and the method further includes:
performing image quality calculation on an image obtained by image super-resolution reconstruction based on a preset evaluation index;
if the image quality data does not meet the preset high-resolution image condition, iteration of the image super-resolution reconstruction process is carried out by changing the variable parameters in the parameterized Thiele continuous fractional interpolation until an image meeting the preset high-resolution image condition is obtained.
And performing color space inverse conversion to restore the original color space, and obtaining a high-resolution and high-quality image.
Based on the above image processing method using parametric Thiele continuous fractional interpolation, an embodiment of the present invention further provides an image processing apparatus using parametric Thiele continuous fractional interpolation, including:
the image channel image extraction unit is used for converting the image to be processed into a color space and extracting a corresponding channel image, wherein the channel image at least comprises a channel representing the image brightness;
the channel image enhancement unit is used for carrying out frequency domain space conversion on different channels, and adopting a matched filtering method based on the characteristics of the different channels to inhibit low-frequency components in a channel frequency spectrum and improve corresponding channel components;
the noise reduction and edge protection unit is used for filtering smooth areas and non-smooth areas of channel images to different degrees through a filter based on different channels with improved components and carrying out a noise reduction process based on edge protection;
the high-resolution channel image acquisition unit is used for carrying out image super-resolution reconstruction by a parameterized Thiele continuous fractional interpolation method based on different channel images to acquire a high-resolution image;
and the channel image fusion unit is used for carrying out color space inverse conversion and recovering to the original color space to obtain a high-resolution and high-quality image.
An embodiment of the present invention further provides an electronic device, which may be implemented in various forms, such as a dedicated terminal with an image processing function, or an electronic device with an image processing function or a cloud server, where the electronic device includes:
a memory for storing executable instructions;
and the processor is used for realizing the image processing method applying the parameterized Thiele continuous fractional interpolation when the executable instructions stored in the memory are run.
It will be appreciated that the memory can be either volatile memory or nonvolatile memory, and can include both volatile and nonvolatile memory. The memory in the embodiment of the present invention can store data to support the operation of the terminal, and examples of the data include: any computer program for operating on a terminal, such as an operating system and application programs. The operating system includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, and is used for implementing various basic services and processing hardware-based tasks. The application program may include various application programs. The image processing apparatus provided in the embodiment of the present invention may be implemented by combining software and hardware, and as an example that the image processing apparatus provided in the embodiment of the present invention is implemented by combining software and hardware, the image processing apparatus provided in the embodiment of the present invention may be directly embodied as a combination of software modules executed by a processor, the software modules may be located in a storage medium, the storage medium is located in a memory, the processor reads executable instructions included in the software modules in the memory, and the image processing method using parameterized Thiele continuous interpolation provided in the embodiment of the present invention is completed by combining necessary hardware.
The present invention is not limited to the above-described embodiments, and those skilled in the art will be able to make various modifications without creative efforts from the above-described conception, and fall within the scope of the present invention.
Claims (10)
1. An image processing method using parameterized Thiele continuous fractional interpolation, characterized in that: the method comprises the following steps:
converting an image to be processed into a color space and extracting a corresponding channel image, wherein the channel image at least comprises a channel representing the brightness of the image;
carrying out frequency domain space conversion on different channels, and adopting a matched filtering method based on the characteristics of the different channels to suppress low-frequency components in a channel frequency spectrum and improve corresponding channel components;
based on different channels with increased components, filtering smooth areas and non-smooth areas of channel images to different degrees through a filter, and carrying out a denoising process based on edge protection;
based on different channel images, carrying out image super-resolution reconstruction by a parameterized Thiele continuous fractional interpolation method to obtain a high-resolution image;
and performing color space inverse conversion to restore the original color space, and obtaining a high-resolution and high-quality image.
2. The image processing method applying parameterized Thiele piecewise interpolation according to claim 1, characterized in that: the formula of the parameterized Thiele continuous fractional interpolation adopts binary Thiele continuous fractional interpolation containing single parameter.
3. The image processing method using parameterized Thiele continuous fractional interpolation according to claim 2, wherein: the binary Thiele continuous fraction interpolation containing single parameter is as follows:
wherein the content of the first and second substances,
j is 0,1,. and n; 1,2,. m; i ═ p, p + 1.., m,
ak,0,ak,1,...,ak,l,
ak,l+1,ak,l+2,...,ak,nin the formula
The calculated value after introducing the parameter lambda.
P is 0, 1., k-1, k +1,.., m; q ═ 1,2,. n; j ═ q, q + 1.., n,
4. the image processing method using parameterized Thiele continuous fractional interpolation according to claim 3, wherein: the image super-resolution reconstruction is carried out through a parameterized Thiele continuous fractional interpolation method to obtain a high-resolution image, different regions are divided based on image gradient change, interpolation is carried out by adopting parameterized Thiele continuous fractional interpolation formulas respectively, and the interpolation formula of each region optimizes the interpolation image based on the adjustment of variable parameters.
5. The image processing method using parameterized Thiele continuous fractional interpolation according to claim 4, wherein: the method for reconstructing the image super-resolution by the parameterized Thiele continuous fractional interpolation method to obtain the high-resolution image further comprises the following steps:
performing image quality calculation on an image obtained by image super-resolution reconstruction based on a preset evaluation index;
if the image quality data does not meet the preset high-resolution image condition, iteration of the image super-resolution reconstruction process is carried out by changing the variable parameters in the parameterized Thiele continuous fractional interpolation until an image meeting the preset high-resolution image condition is obtained.
6. The image processing method applying parameterized Thiele piecewise interpolation according to claim 1, characterized in that: the method comprises the steps of converting an image to be processed into a color space and extracting a corresponding channel image, specifically converting the image from RGB into HSV color space.
7. The image processing method using parameterized Thiele continuous fractional interpolation according to claim 6, wherein: the frequency domain space conversion is carried out on different channels, a matched filtering method is adopted based on the characteristics of the different channels, the low-frequency component in the channel frequency spectrum is suppressed, and the corresponding channel component is improved, and the method comprises the following steps:
sliding the S-channel image and the V-channel image based on a preset sliding window, and performing homomorphic filtering on an image area in each sliding window, wherein the homomorphic filtering cut-off frequency of each image area is matched with the frequency spectrum of the image area;
and merging the homomorphically filtered images of all the sliding window image areas to obtain an S-channel image with enhanced saturation and a V-channel image with enhanced brightness contrast.
8. The image processing method using parameterized Thiele continuous fractional interpolation according to claim 6, wherein: the filtering of different degrees is carried out on the smooth region and the non-smooth region of the channel image through the filter, and the denoising process based on the edge protection is carried out, and comprises the following steps:
filtering based on a filter model, wherein the model is as follows:
parameter a of the modelp′,bp′Satisfying the objective optimization function E:
wherein G is a guide map, X is an image before filtering, G and X are allowed to be the same,
is a window with p' as the center and ζ 1 as the radius,
is a filtered image, ap′And bp′Is that
Two constants in the window are set to be constant,
is the edge perceptual weight, which is the local variance ratio of all pixels of a 3x3 window pixel and (2 ζ 1+1) x (2 ζ 1+1) window, χ (p') ═ σG,1(p′)σG,ζ1(p′)，σG,1(p') and σG,ζ1(p') respectively show the image G in the window omega1(p') and
standard deviation of (0.001 x L)2L is the dynamic range of image X; k is a constant; var (x (p) -x (p ') represents the difference between the variance of x (p) and x (p'); var (x (p) -min (x (p)) represents the difference between the variance of x (p) and the minimum value of x (p).
9. An image processing apparatus using a parametric Thiele continuous fractional interpolation, characterized in that: the method comprises the following steps:
the image channel image extraction unit is used for converting the image to be processed into a color space and extracting a corresponding channel image, wherein the channel image at least comprises a channel representing the image brightness;
the channel image enhancement unit is used for carrying out frequency domain space conversion on different channels, and adopting a matched filtering method based on the characteristics of the different channels to inhibit low-frequency components in a channel frequency spectrum and improve corresponding channel components;
the noise reduction and edge protection unit is used for filtering smooth areas and non-smooth areas of channel images to different degrees through a filter based on different channels with improved components and carrying out a noise reduction process based on edge protection;
the high-resolution channel image acquisition unit is used for carrying out image super-resolution reconstruction by a parameterized Thiele continuous fractional interpolation method based on different channel images to acquire a high-resolution image;
and the channel image fusion unit is used for carrying out color space inverse conversion and recovering to the original color space to obtain a high-resolution and high-quality image.
10. An electronic device, characterized in that the electronic device comprises:
a memory for storing executable instructions;
a processor for implementing the image processing method applying parameterized Thiele continuous fraction interpolation of any one of claims 1 to 8 when executing the executable instructions stored in the memory.
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