CN110910439A - Image resolution estimation method and device and terminal - Google Patents
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Abstract
The embodiment of the application discloses an image resolution estimation method, an image resolution estimation device, a terminal and a storage medium, wherein the method comprises the following steps: acquiring an image to be estimated output by a main processing module of an intelligent image processing terminal; calculating the brightness value of each pixel point in the image to be estimated; calculating the energy value of a frequency pair corresponding to each pixel point according to the brightness value, and calculating a first total energy value of the image to be estimated according to the energy values of the frequency pairs; calculating the proportion of second total energy values of all frequency pairs with frequencies above a preset frequency in the image to be estimated in the first total energy value; and estimating the resolution of the image to be estimated by judging the size between the ratio and the first preset ratio threshold value and the second preset ratio threshold value. By the embodiment of the application, the resolution estimation of the image output by the main processing module of the intelligent image processing terminal can be realized, and a basis is provided for the next image processing.
Description
Technical Field
The present application belongs to the field of image processing technologies, and in particular, to an image resolution estimation method, an image resolution estimation device, an intelligent image processing terminal, and a computer-readable storage medium.
Background
With the development and progress of image processing technology, the application of intelligent image processing equipment such as digital televisions and the like is more and more extensive.
At present, videos with different original resolutions can output images with corresponding resolutions after passing through a main processing module of intelligent image processing equipment, and the images are displayed through the intelligent image processing equipment after being further processed. Images with different original resolutions need to be processed differently, but the original resolution of the image processed by the main processing module is generally not easily obtained under the structure of the existing intelligent image processing device. For example, for a smart television, image data processed by an SOC chip of the smart television is difficult to obtain an original resolution of an input image of the smart television due to an existing structure of the smart television.
Disclosure of Invention
In view of the above, embodiments of the present application provide an image resolution estimation method, an image resolution estimation device, an intelligent image processing terminal, and a computer readable storage medium, so as to estimate an original resolution of an image output by a main processing module of the intelligent image processing terminal.
A first aspect of an embodiment of the present application provides an image resolution estimation method, including:
acquiring an image to be estimated output by a main processing module of an intelligent image processing terminal;
calculating the brightness value of each pixel point in the image to be estimated;
calculating the energy value of a frequency pair corresponding to each pixel point according to the brightness value, and calculating a first total energy value of the image to be estimated according to the energy value of the frequency pair;
calculating the proportion of second total energy values of frequency pairs with frequencies above a preset frequency in the image to be estimated in the first total energy value;
and estimating the resolution of the image to be estimated by judging the size between the ratio and a first preset ratio threshold value and a second preset ratio threshold value.
Optionally, estimating the resolution of the image to be estimated by determining a size between the ratio and a first preset ratio threshold and a second preset ratio threshold, including:
judging the size between the ratio and the first preset ratio threshold value and the second preset ratio threshold value; wherein the first preset proportion threshold is greater than the second preset proportion threshold;
when the proportion is larger than the first preset proportion threshold value, the resolution of the image to be estimated is obtained as a first resolution;
when the ratio is greater than the second preset ratio threshold and less than or equal to the first preset ratio threshold, obtaining that the resolution of the image to be estimated is a second resolution;
and when the proportion is less than or equal to the second preset proportion threshold value, obtaining that the resolution of the image to be traced is a third resolution.
Optionally, calculating an energy value of a frequency pair corresponding to each pixel point according to the brightness value, and calculating a first total energy value of the image to be estimated according to the energy values of the frequency pairs, including:
setting the expression I (x, y) of the luminance value to 0.299Ir(x,y)+0.587Ig(x,y)+0.114Ib(x, y) transforms into two-dimensional discrete Fourier expressions
Wherein (X, Y) is the coordinate of the pixel point of the image to be estimated, X is more than or equal to 1 and less than or equal to X, Y is more than or equal to 1 and less than or equal to Y, and X, Y are positive integers; i isr(x, y) is the value of the red color of the image to be estimated at point (x, y); i isg(x, y) is the value of green at point (x, y) of the image to be estimated; i isb(x, y) is a value of blue color of the image to be estimated at point (x, y); i (x, y) is the brightness value of the image to be estimated at the point (x, y); (omega)x,ωy) Is the frequency pair corresponding to the pixel point (x, y), 1 is not more than omegax≤X，1≤ωy≤Y；
According to the formula E (ω)x,ωy)＝|F(ωx,ωy)|2Calculating an energy value E (ω) for each of said frequency pairsx,ωy)；
Energy value E (ω) according to each of said frequency pairsx,ωy) And formula
And calculating a first total energy value of the image to be estimated.
Optionally, the brightness value is adjustedExpression I (x, y) ═ 0.299Ir(x,y)+0.587Ig(x,y)+0.114Ib(x, y) transforms into two-dimensional discrete Fourier expressions
The method comprises the following steps:
using fast Fourier transform algorithm, the expression I (x, y) of the brightness value is equal to 0.299Ir(x,y)+0.587Ig(x,y)+0.114Ib(x, y) transforms into two-dimensional discrete Fourier expressions
Optionally, calculating a ratio of a second total energy value of each frequency pair with a frequency above a preset frequency in the image to be estimated to the first total energy value includes:
using formulas
Calculating the proportion of the second energy value to the first total energy value; wherein A is the ratio, ωHIn order to be the said preset frequency,
is the second total energy value.
A second aspect of an embodiment of the present application provides an image resolution estimation apparatus, including:
the acquisition module is used for acquiring an image to be estimated output by a main processing module of the intelligent image processing terminal;
the brightness value calculation module is used for calculating the brightness value of each pixel point in the image to be estimated;
the energy value calculation module is used for calculating the energy value of the frequency pair corresponding to each pixel point according to the brightness value and calculating a first total energy value of the image to be estimated according to the energy value of the frequency pair;
the proportion calculation module is used for calculating the proportion of second total energy values of frequency pairs with frequencies above a preset frequency in the image to be estimated in the first total energy value;
and the estimation module is used for estimating the resolution of the image to be estimated by judging the size between the ratio and a first preset ratio threshold value and a second preset ratio threshold value.
Optionally, the estimation module comprises:
the judging unit is used for judging the size between the proportion and the first preset proportion threshold value and between the proportion and the second preset proportion threshold value; wherein the first preset proportion threshold is greater than the second preset proportion threshold;
a first deriving unit, configured to derive a resolution of the image to be estimated as a first resolution when the ratio is greater than the first preset ratio threshold;
a second obtaining unit, configured to obtain, when the ratio is greater than the second preset ratio threshold and is less than or equal to the first preset ratio threshold, that the resolution of the image to be estimated is a second resolution;
and the third obtaining unit is used for obtaining that the resolution of the image to be traced is a third resolution when the proportion is less than or equal to the second preset proportion threshold.
Optionally, the energy value calculation module comprises:
a transforming unit for setting an expression I (x, y) of the luminance value to 0.299Ir(x,y)+0.587Ig(x,y)+0.114Ib(x, y) transforms into two-dimensional discrete Fourier expressions
Wherein (X, Y) is the coordinate of the pixel point of the image to be estimated, X is more than or equal to 1 and less than or equal to X, Y is more than or equal to 1 and less than or equal to Y, and X, Y are positive integers; i isr(x, y) is the value of the red color of the image to be estimated at point (x, y); i isg(x, y) is the value of green at point (x, y) of the image to be estimated; i isb(x, y) is a value of blue color of the image to be estimated at point (x, y); i (x, y) is the brightness value of the image to be estimated at the point (x, y); (omega)x,ωy) Is the frequency pair corresponding to the pixel point (x, y), 1 is not more than omegax≤X，1≤ωy≤Y；
A first calculation unit for calculating (ω) according to the formula Ex,ωy)＝|F(ωx,ωy)|2Calculating an energy value E (ω) for each of said frequency pairsx,ωy)；
A second calculation unit for calculating an energy value E (ω) according to each of the frequency pairsx,ωy) And formula
And calculating a first total energy value of the image to be estimated.
A third aspect of embodiments of the present application provides an intelligent image processing terminal, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the method according to any one of the above first aspects when executing the computer program.
A fourth aspect of embodiments of the present application provides a computer-readable storage medium, in which a computer program is stored, which, when executed by a processor, performs the steps of the method according to any one of the above first aspects.
Compared with the prior art, the embodiment of the application has the advantages that:
according to the embodiment of the application, based on the principle that the proportion of high-frequency components of an image with high original resolution in signal energy is high and the proportion of high-frequency components of an image with low resolution is low, the energy value of a frequency pair corresponding to each pixel point of an image to be estimated is calculated, the total energy value of the image to be estimated is calculated according to the energy value of each point, the total energy value of each point with the frequency above a preset frequency is calculated, the proportion of the energy of the high-frequency components in the total energy is calculated, the resolution of the image to be estimated is estimated according to the proportion, the resolution estimation of the image output by a main processing module of an intelligent image processing terminal is realized, and a basis is provided for the next image processing.
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In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flowchart of an image resolution estimation method according to an embodiment of the present disclosure;
fig. 2 is another schematic flow chart of an image resolution estimation method according to an embodiment of the present disclosure;
fig. 3 is a schematic block diagram of a structure of an image resolution estimation apparatus according to an embodiment of the present application;
fig. 4 is a schematic diagram of an intelligent image processing terminal according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
In order to explain the technical solution described in the present application, the following description will be given by way of specific examples.
Example one
Referring to fig. 1, a schematic flow chart of an image resolution estimation method provided in an embodiment of the present application is applied to an intelligent image processing terminal, and the method may specifically include the following steps:
and S101, acquiring an image to be estimated output by a main processing module of the intelligent image processing terminal.
It should be noted that the intelligent image processing terminal refers to an intelligent image processing device for processing an image, and specifically may be a terminal such as a smart television, a smart phone, or a smart tablet, and the main processing module refers to a main chip in the terminal. At present, the original resolution of an image output by a main processing module of an intelligent image processing terminal is difficult to obtain. For example, when the intelligent image processing terminal is an intelligent television, the main processing module is specifically an SOC chip, and an image processed by the SOC chip needs to be input to the intelligent television, but the original resolution of the image processed by the SOC chip is difficult to obtain at present. Of course, the intelligent image processing terminal is not limited to the intelligent television, and may be other, and is not limited herein.
And S102, calculating the brightness value of each pixel point in the image to be estimated.
In a specific application, the formula I (x, y) ═ 0.299I can be usedr(x,y)+0.587Ig(x,y)+0.114Ib(x, y) calculating the brightness value of each pixel point, wherein the brightness value is the average value of the sum of the red component, the green component and the blue component of each pixel point. Wherein (X, Y) is the coordinate of the pixel point of the image to be estimated, X is more than or equal to 1 and less than or equal to X, Y is more than or equal to 1 and less than or equal to Y, and X, Y are positive integers; i isr(x, y) is the value of the red color of the image to be estimated at point (x, y); i isg(x, y) is the value of green at point (x, y) of the image to be estimated; i isb(x, y) is the value of blue color of the image to be estimated at point (x, y); i (x, y) is the luminance value of the image to be estimated at point (x, y).
Of course, the brightness value may be calculated by using other brightness value calculation formulas besides the above formula, as long as the brightness value of each pixel point can be calculated, which is not limited herein.
Step S103, calculating the energy value of the frequency pair corresponding to each pixel point according to the brightness value, and calculating a first total energy value of the image to be estimated according to the energy value of the frequency pair.
Specifically, the formula of the luminance value may be first transformed into a two-dimensional discrete fourier expression to represent the signal energy of each pixel in the frequency domain, and the pixel (x, y) is transformed into the frequency domain and then correspondingly becomes a frequency pair (ω)x,ωy) (ii) a Then calculating the square of the modulus of the Fourier expression, and taking the square as the energy value of the frequency pair; calculating energy values of frequency pairs corresponding to each pixel point in the image to be estimated according to the frequency pairs; and then, calculating a first total energy value of the whole image according to the energy values of the frequency pairs.
And step S104, calculating the proportion of second total energy values of all frequency pairs with frequencies above a preset frequency in the image to be estimated to the first total energy values.
It should be noted that the preset frequency refers to a pre-selected frequency, which can be set according to the actual parameters of the intelligent image processing terminal. For example, when the intelligent image processing terminal is an intelligent television, the preset frequency may be selected according to a television system supported by the intelligent television, that is, the preset frequency is selected according to different television systems. Generally, above a predetermined frequency ωHCan identify high frequency components below a predetermined frequency omegaHCan be considered as a low frequency component.
Specifically, the frequency ω higher than the preset frequency in the image may be calculated firstHAnd then the ratio of the second total energy to the first total energy is calculated.
And S105, estimating the resolution of the image to be estimated by judging the size between the ratio and the first preset ratio threshold value and the second preset ratio threshold value.
It should be noted that, both the first preset proportion threshold and the second preset proportion threshold may be set according to actual parameters of the intelligent image processing terminal. For example, when the intelligent image processing terminal is an intelligent television, the first preset proportion threshold and the second preset proportion threshold may be selected according to television systems supported by the intelligent television, that is, the first preset proportion threshold and the second preset proportion threshold are selected according to different television systems correspondingly.
And calculating the energy distribution in the frequency domain of the image to be estimated so as to estimate the original resolution of the image to be estimated and provide a basis for the next image processing. The method is mainly characterized in that according to an image with high original resolution, the proportion of high-frequency components in the image in signal energy is high, and the proportion of high-frequency components in the image in signal energy is low. Therefore, the resolution of the image to be estimated can be estimated by determining within which range the ratio of the energy value of the high-frequency component to the total energy value falls.
In specific application, the first preset proportion threshold is larger than the second preset proportion threshold, and when the proportion is larger than the first preset proportion, the resolution of the image to be estimated is judged to be the first resolution; when the ratio is greater than a second preset ratio threshold and smaller than a first preset ratio threshold, judging that the resolution of the image to be estimated is a second resolution; and when the proportion is smaller than a second preset proportion threshold value, judging that the resolution of the image to be estimated is a third resolution.
In this embodiment, based on the principle that the proportion of the high-frequency component of the image with high original resolution in the signal energy is high and the proportion of the high-frequency component of the image with low resolution is low, the energy value of the frequency pair corresponding to each pixel point of the image to be estimated is calculated, the total energy value of the image to be estimated is calculated according to the energy value of each point, the total energy value of each point with the frequency above the preset frequency is calculated, the proportion of the energy of the high-frequency component in the total energy is calculated, the resolution of the image to be estimated is estimated according to the size of the proportion, the resolution estimation of the image output by the main processing module of the intelligent image processing terminal is realized, and a basis is provided for the next image processing.
Example two
Referring to fig. 2, another flow chart of an image resolution estimation method according to an embodiment of the present disclosure is shown, where the method specifically includes the following steps:
step S201, obtaining an image to be estimated output by a main processing module of the intelligent image processing terminal.
Step S202, calculating the brightness value of each pixel point in the image to be estimated.
It is to be understood that steps S201 to S202 are the same as steps S101 to S102 in the first embodiment, and specific reference may be made to corresponding descriptions in the first embodiment, which are not repeated herein.
Step S203, change the expression I (x, y) of the luminance value to 0.299Ir(x,y)+0.587Ig(x,y)+0.114Ib(x, y) transforms into two-dimensional discrete Fourier expressions
Wherein (X, Y) is the coordinate of the pixel point of the image to be estimated, X is more than or equal to 1 and less than or equal to X, Y is more than or equal to 1 and less than or equal to Y, and X, Y are positive integers; i isr(x, y) is the value of the red color of the image to be estimated at point (x, y); i isg(x, y) is the value of green at point (x, y) of the image to be estimated; i isb(x, y) is the value of blue color of the image to be estimated at point (x, y); i (x, y) is the brightness value of the image to be estimated at the point (x, y); (omega)x,ωy) Is the frequency pair corresponding to the pixel point (x, y), 1 is not more than omegax≤X，1≤ωy≤Y。
In a specific application, in order to reduce the amount of calculation and improve the calculation efficiency, the step can be implemented by using a fast fourier transform algorithm. That is, in some embodiments of the present application, the present step may be, for example: using fast Fourier transform algorithm, the expression of brightness value I (x, y) is 0.299Ir(x,y)+0.587Ig(x,y)+0.114Ib(x, y) transforms into two-dimensional discrete Fourier expressions
Thus, the calculation amount in the transformation process can be reduced to a certain extent. Of course, the transformation process may also be specifically implemented by other algorithms, and is not limited herein.
Step S204, according to formula E (omega)x,ωy)＝|F(ωx,ωy)|2Calculating the energy value E (omega) of each frequency pairx,ωy)。
Step S205, energy value E (omega) according to each frequency pairx,ωy) And formula
And calculating a first total energy value of the image to be estimated.
Step S206, using formula
Calculating the proportion of the second energy value in the first total energy value; wherein A is a ratio, ωHIn order to set the frequency to a predetermined value,
is the second total energy value.
Step S207, judging the size between the proportion and a first preset proportion threshold value and a second preset proportion threshold value; the first preset proportion threshold value is larger than the second preset proportion threshold value; when the proportion is larger than a first preset proportion threshold value, obtaining that the resolution of the image to be estimated is a first resolution; when the proportion is greater than a second preset proportion threshold value and less than or equal to a first preset proportion threshold value, obtaining that the resolution of the image to be estimated is a second resolution; and when the proportion is less than or equal to a second preset proportion threshold value, obtaining that the resolution of the image to be traced is a third resolution.
For example, when the intelligent image processing terminal is an intelligent television, the preset frequency ω can be selected according to different television systemsHAnd a range to estimate the resolution of the image. For a 1920x1080 smart television, selecting a preset frequency omegaHThe first preset scaling threshold is 0.05 and the second preset scaling threshold is 0.02, 30. When A is>0.05, the original resolution of the image to be estimated is 1920x1080 (first resolution); when 0.02<When A is less than or equal to 0.05, the original resolution of the image to be estimated is 1280x720 (second resolution); when A is less than or equal to 0.02, the original resolution of the image to be estimated is 853x480 (third resolution).
It should be noted that, for different television systems (e.g. television systems with different resolutions), the preset frequency ω is setHThe first preset proportion threshold, the second preset proportion threshold, the first resolution, the second resolution and the third resolution may be changed accordingly.
Specifically, the first resolution,The second resolution and the third resolution can be set by the technicians in the field, and the values of the second resolution and the third resolution can be conventional standard resolutions in the fields of videos and images; while the preset frequency omegaHThe first preset proportion threshold value and the second preset proportion threshold value are obtained by processing a large number of images with the determined first resolution, second resolution and third resolution through the selected television system after the specific television system is selected, and omega can be manually specifiedHThen, the value at ω can be calculatedHThe second total energy value of each frequency pair is statistically distributed in the proportion of the first total energy value, and then the first preset proportion threshold and the second preset proportion threshold are reasonably set according to the statistical distribution, so that the original resolution of the image can be estimated according to the size relation between the proportion and the first preset proportion threshold and the second preset proportion threshold when the image is processed subsequently.
In this embodiment, based on the principle that the proportion of the high-frequency component of the image with high original resolution in the signal energy is high and the proportion of the high-frequency component of the image with low resolution is low, the energy value of the frequency pair corresponding to each pixel point of the image to be estimated is calculated, the total energy value of the image to be estimated is calculated according to the energy value of each point, the total energy value of each point with the frequency above the preset frequency is calculated, the proportion of the energy of the high-frequency component in the total energy is calculated, the resolution of the image to be estimated is estimated according to the size of the proportion, the resolution estimation of the image output by the main processing module of the intelligent image processing terminal is realized, and a basis is provided for the next image processing.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
EXAMPLE III
Referring to fig. 3, a schematic block diagram of a structure of an image resolution estimation apparatus provided in an embodiment of the present application, the apparatus being specifically integrated in an intelligent image processing terminal, and the apparatus may include:
the acquiring module 31 is used for acquiring an image to be estimated output by a main processing module of the intelligent image processing terminal;
the brightness value calculation module 32 is configured to calculate a brightness value of each pixel point in the image to be estimated;
the energy value calculation module 33 is configured to calculate an energy value of a frequency pair corresponding to each pixel point according to the brightness value, and calculate a first total energy value of the image to be estimated according to the energy value of the frequency pair;
the proportion calculation module 34 is used for calculating the proportion of second total energy values of frequency pairs with frequencies above a preset frequency in the image to be estimated in the first total energy value;
the estimation module 35 is configured to estimate the resolution of the image to be estimated by determining a size between the ratio and the first preset ratio threshold and the second preset ratio threshold.
In some embodiments of the present application, the estimation module may include:
the judging unit is used for judging the size between the proportion and a first preset proportion threshold value and between the proportion and a second preset proportion threshold value; the first preset proportion threshold value is larger than the second preset proportion threshold value;
the first obtaining unit is used for obtaining that the resolution of the image to be estimated is a first resolution when the proportion is larger than a first preset proportion threshold;
the second obtaining unit is used for obtaining that the resolution of the image to be estimated is a second resolution when the proportion is greater than a second preset proportion threshold and less than or equal to a first preset proportion threshold;
and the third obtaining unit is used for obtaining that the resolution of the image to be traced is a third resolution when the proportion is less than or equal to a second preset proportion threshold.
In some embodiments of the present application, the energy value calculating module may include:
a transforming unit for changing the expression I (x, y) of the luminance value to 0.299Ir(x,y)+0.587Ig(x,y)+0.114Ib(x, y) transforms into two-dimensional discrete Fourier expressions
Wherein (X, Y) is the coordinate of the pixel point of the image to be estimated, X is more than or equal to 1 and less than or equal to X, Y is more than or equal to 1 and less than or equal to Y, and X, Y are positive integers; i isr(x, y) is the value of the red color of the image to be estimated at point (x, y); i isg(x, y) is the value of green at point (x, y) of the image to be estimated; i isb(x, y) is the value of blue color of the image to be estimated at point (x, y); i (x, y) is the brightness value of the image to be estimated at the point (x, y); (omega)x,ωy) Is the frequency pair corresponding to the pixel point (x, y), 1 is not more than omegax≤X，1≤ωy≤Y；
A first calculation unit for calculating (ω) according to the formula Ex,ωy)＝|F(ωx,ωy)|2Calculating the energy value E (omega) of each frequency pairx,ωy)；
A second calculation unit for calculating energy values E (ω) according to the respective frequency pairsx,ωy) And formula
And calculating a first total energy value of the image to be estimated.
Further, the transformation unit may include:
a fast transform subunit for converting the expression I (x, y) of the luminance value to 0.299I using a fast fourier transform algorithmr(x,y)+0.587Ig(x,y)+0.114Ib(x, y) transforms into two-dimensional discrete Fourier expressions
In some embodiments of the present application, the proportion calculation module may include:
a third calculation unit for using the formula
Calculating the proportion of the second energy value in the first total energy value; wherein A is a ratio, ωHIn order to set the frequency to a predetermined value,
is the second total energy value.
In this embodiment, based on the principle that the proportion of the high-frequency component of the image with high original resolution in the signal energy is high and the proportion of the high-frequency component of the image with low resolution is low, the energy value of the frequency pair corresponding to each pixel point of the image to be estimated is calculated, the total energy value of the image to be estimated is calculated according to the energy value of each point, the total energy value of each point with the frequency above the preset frequency is calculated, the proportion of the energy of the high-frequency component in the total energy is calculated, the resolution of the image to be estimated is estimated according to the size of the proportion, the resolution estimation of the image output by the main processing module of the intelligent image processing terminal is realized, and a basis is provided for the next image processing.
Example four
Fig. 4 is a schematic diagram of an intelligent image processing terminal according to an embodiment of the present application. As shown in fig. 4, the intelligent image processing terminal 4 of this embodiment includes: a processor 40, a memory 41 and a computer program 42,. The processor 40, when executing the computer program 42, implements the steps in the various image resolution estimation method embodiments described above, such as the steps S101 to S105 shown in fig. 1. Alternatively, the processor 40, when executing the computer program 42, implements the functions of each module or unit in each device embodiment described above, for example, the functions of the modules 31 to 35 shown in fig. 3.
Illustratively, the computer program 42 may be partitioned into one or more modules or units that are stored in the memory 41 and executed by the processor 40 to accomplish the present application. The one or more modules or units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program 42 in the intelligent image processing terminal 4. For example, the computer program 42 may be divided into an acquisition module, a brightness value calculation module, an energy value calculation module, a proportion calculation module, and an estimation module, each module having the following specific functions:
the acquisition module is used for acquiring an image to be estimated output by a main processing module of the intelligent image processing terminal;
the brightness value calculation module is used for calculating the brightness value of each pixel point in the image to be estimated;
the energy value calculation module is used for calculating the energy value of the frequency pair corresponding to each pixel point according to the brightness value and calculating a first total energy value of the image to be estimated according to the energy value of the frequency pair;
the proportion calculation module is used for calculating the proportion of second total energy values of all frequency pairs with frequencies above a preset frequency in the image to be estimated in the first total energy value;
and the estimation module is used for estimating the resolution of the image to be estimated by judging the size between the proportion and the first preset proportion threshold value and the second preset proportion threshold value.
The intelligent image processing terminal 4 can be an intelligent television or other image processing terminals. The intelligent image processing terminal may include, but is not limited to, a processor 40, a memory 41. It will be understood by those skilled in the art that fig. 4 is only an example of the intelligent image processing terminal 4, and does not constitute a limitation to the intelligent image processing terminal 4, and may include more or less components than those shown, or combine some components, or different components, for example, the intelligent image processing terminal may further include an input-output device, a network access device, a bus, etc.
The Processor 40 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 41 may be an internal storage unit of the intelligent image processing terminal 4, such as a hard disk or a memory of the intelligent image processing terminal 4. The memory 41 may also be an external storage device of the intelligent image processing terminal 4, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the intelligent image processing terminal 4. Further, the memory 41 may also include both an internal storage unit and an external storage device of the intelligent image processing terminal 4. The memory 41 is used to store the computer program and other programs and data required by the intelligent image processing terminal. The memory 41 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus, terminal and method may be implemented in other ways. For example, the above-described apparatus and terminal embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules or units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method of the embodiments described above can be realized by a computer program, which can be stored in a computer-readable storage medium and can realize the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (10)
1. An image resolution estimation method, comprising:
acquiring an image to be estimated output by a main processing module of an intelligent image processing terminal;
calculating the brightness value of each pixel point in the image to be estimated;
calculating the energy value of a frequency pair corresponding to each pixel point according to the brightness value, and calculating a first total energy value of the image to be estimated according to the energy value of the frequency pair;
calculating the proportion of second total energy values of frequency pairs with frequencies above a preset frequency in the image to be estimated in the first total energy value;
and estimating the resolution of the image to be estimated by judging the size between the ratio and a first preset ratio threshold value and a second preset ratio threshold value.
2. The method of claim 1, wherein estimating the resolution of the image to be estimated by determining a size between the ratio and a first preset ratio threshold and a second preset ratio threshold comprises:
judging the size between the ratio and the first preset ratio threshold value and the second preset ratio threshold value; wherein the first preset proportion threshold is greater than the second preset proportion threshold;
when the proportion is larger than the first preset proportion threshold value, the resolution of the image to be estimated is obtained as a first resolution;
when the ratio is greater than the second preset ratio threshold and less than or equal to the first preset ratio threshold, obtaining that the resolution of the image to be estimated is a second resolution;
and when the proportion is less than or equal to the second preset proportion threshold value, obtaining that the resolution of the image to be traced is a third resolution.
3. The method according to claim 1 or 2, wherein calculating an energy value of a frequency pair corresponding to each pixel point based on the luminance value, and calculating a first total energy value of the image to be estimated based on the energy values of the frequency pairs, comprises:
setting the expression I (x, y) of the luminance value to 0.299Ir(x,y)+0.587Ig(x,y)+0.114Ib(x, y) transforms into two-dimensional discrete Fourier expressions
Wherein (X, Y) is the coordinate of the pixel point of the image to be estimated, X is more than or equal to 1 and less than or equal to X, Y is more than or equal to 1 and less than or equal to Y, and X, Y are positive integers; i isr(x, y) is the value of the red color of the image to be estimated at point (x, y); i isg(x, y) is the value of green at point (x, y) of the image to be estimated; i isb(x, y) is a value of blue color of the image to be estimated at point (x, y); i (x, y) is the brightness value of the image to be estimated at the point (x, y); (omega)x,ωy) Is the frequency pair corresponding to the pixel point (x, y), 1 is not more than omegax≤X，1≤ωy≤Y；
According to the formula E (ω)x,ωy)＝|F(ωx,ωy)|2Calculating an energy value E (ω) for each of said frequency pairsx,ωy)；
Energy value E (ω) according to each of said frequency pairsx,ωy) And formula
And calculating a first total energy value of the image to be estimated.
4. A method as claimed in claim 3, characterized by changing the expression I (x, y) of the luminance value to 0.299Ir(x,y)+0.587Ig(x,y)+0.114Ib(x, y) transforms into two-dimensional discrete Fourier expressions
The method comprises the following steps:
using fast Fourier transform algorithm, the expression I (x, y) of the brightness value is equal to 0.299Ir(x,y)+0.587Ig(x,y)+0.114Ib(x, y) transforms into two-dimensional discrete Fourier expressions
5. The method of claim 3, wherein calculating a ratio of a second total energy value to the first total energy value for each frequency pair having a frequency above a predetermined frequency in the image to be estimated comprises:
using formulas
Calculating the proportion of the second energy value to the first total energy value; wherein A is the ratio, ωHIn order to be the said preset frequency,
is the second total energy value.
6. An image resolution estimating apparatus, characterized by comprising:
the acquisition module is used for acquiring an image to be estimated output by a main processing module of the intelligent image processing terminal;
the brightness value calculation module is used for calculating the brightness value of each pixel point in the image to be estimated;
the energy value calculation module is used for calculating the energy value of the frequency pair corresponding to each pixel point according to the brightness value and calculating a first total energy value of the image to be estimated according to the energy value of the frequency pair;
the proportion calculation module is used for calculating the proportion of second total energy values of frequency pairs with frequencies above a preset frequency in the image to be estimated in the first total energy value;
and the estimation module is used for estimating the resolution of the image to be estimated by judging the size between the ratio and a first preset ratio threshold value and a second preset ratio threshold value.
7. The apparatus of claim 6, wherein the estimation module comprises:
the judging unit is used for judging the size between the proportion and the first preset proportion threshold value and between the proportion and the second preset proportion threshold value; wherein the first preset proportion threshold is greater than the second preset proportion threshold;
a first deriving unit, configured to derive a resolution of the image to be estimated as a first resolution when the ratio is greater than the first preset ratio threshold;
a second obtaining unit, configured to obtain, when the ratio is greater than the second preset ratio threshold and is less than or equal to the first preset ratio threshold, that the resolution of the image to be estimated is a second resolution;
and the third obtaining unit is used for obtaining that the resolution of the image to be traced is a third resolution when the proportion is less than or equal to the second preset proportion threshold.
8. The apparatus of claim 6 or 7, wherein the energy value calculation module comprises:
a transforming unit for setting an expression I (x, y) of the luminance value to 0.299Ir(x,y)+0.587Ig(x,y)+0.114Ib(x, y) transforms into two-dimensional discrete Fourier expressions
Wherein (X, Y) is the coordinate of the pixel point of the image to be estimated, X is more than or equal to 1 and less than or equal to X, Y is more than or equal to 1 and less than or equal to Y, and X, Y are positive integers; i isr(x, y) is the value of the red color of the image to be estimated at point (x, y); i isg(x, y) is the value of green at point (x, y) of the image to be estimated; i isb(x, y) is a value of blue color of the image to be estimated at point (x, y); i (x, y) is the brightness value of the image to be estimated at the point (x, y); (omega)x,ωy) Is the frequency pair corresponding to the pixel point (x, y), 1 is not more than omegax≤X，1≤ωy≤Y；
A first calculation unit for calculating (ω) according to the formula Ex,ωy)＝|F(ωx,ωy)|2Calculating an energy value E (ω) for each of said frequency pairsx,ωy)；
A second calculation unit for calculating an energy value E (ω) according to each of the frequency pairsx,ωy) And formula
And calculating a first total energy value of the image to be estimated.
9. An intelligent image processing terminal, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the method according to any one of claims 1 to 5 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 5.
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