WO2019128539A1

WO2019128539A1 - Image definition obtaining method and apparatus, storage medium, and electronic device

Info

Publication number: WO2019128539A1
Application number: PCT/CN2018/116446
Authority: WO
Inventors: 张乐
Original assignee: Oppo广东移动通信有限公司
Priority date: 2017-12-28
Filing date: 2018-11-20
Publication date: 2019-07-04
Also published as: CN108198189B; CN108198189A

Abstract

Disclosed in the present application is an image definition obtaining method, comprising: obtaining an original image obtained by photographing based on a Bayer array; determining a target region from the original image, and determining distribution positions of pixels with a preset color in the target region; obtaining squared values of difference values of brightness values of the pixels with the preset color in the target region, wherein a relationship of the distribution positions of the pixels is that the pixels are diagonally adjacent; and performing addition on the square values of all the difference values to obtain a sum value, and determining the sum value as the definition of the image.

Description

Method, device, storage medium and electronic device for acquiring picture clarity

This application claims the priority of the Chinese patent application filed on December 28, 2017, the Chinese Patent Office, the application number is 201711464337.8, and the application name is "acquisition method, device, storage medium and electronic device for picture clarity". This is incorporated herein by reference.

Technical field

The present application belongs to the field of image processing technologies, and in particular, to a method, an apparatus, a storage medium, and an electronic device for acquiring picture sharpness.

Background technique

In the process of taking a picture, the electronic device needs to evaluate the picture obtained by the camera module. In the related art, the electronic device can perform a sharpness evaluation on a picture using a sharpness evaluation algorithm. For example, commonly used definition evaluation algorithms include Sobel operators and the like.

Summary of the invention

The embodiment of the present application provides a method, an apparatus, a storage medium, and an electronic device for acquiring picture sharpness, which can improve the efficiency of acquiring picture clarity.

An embodiment of the present application provides a method for acquiring picture clarity, including:

Obtaining the original image taken based on the Bayer array;

Determining a target area from the original picture, and determining a distribution position of pixels of a preset color from the target area;

Obtaining a square value of a difference value of a luminance value of a pixel of a preset color in a diagonally adjacent preset color position in the target area;

The sum of the squared values of all the differences is obtained to obtain a sum value, and the sum value is determined as the sharpness of the picture.

An embodiment of the present application provides a device for acquiring picture sharpness, including:

a first acquiring module, configured to acquire an original picture obtained by shooting according to a Bayer array;

a first determining module, configured to determine a target area from the original picture, and determine a distribution position of a pixel of a preset color from the target area;

a second acquiring module, configured to acquire a square value of a difference value of a luminance value of a pixel of a preset color in which the distribution position relationship in the target area is diagonally adjacent;

And a second determining module, configured to add the square values of all the difference values to obtain a sum value, and determine the sum value as the sharpness of the picture.

The embodiment of the present application provides a storage medium on which a computer program is stored. When the computer program is executed on a computer, the computer is caused to execute the flow in the method for acquiring picture sharpness provided by the embodiment of the present application.

The embodiment of the present application further provides an electronic device, including a memory, a processor, by using a computer program stored in the memory, to execute:

Obtaining the original image taken based on the Bayer array;

DRAWINGS

The technical solutions of the present application and the beneficial effects thereof will be apparent from the detailed description of the specific embodiments of the present application.

FIG. 1 is a schematic flowchart diagram of a method for acquiring picture sharpness provided by an embodiment of the present application.

FIG. 2 is a schematic diagram of pixel distribution of a target area in an original picture provided by an embodiment of the present application.

FIG. 3 is another schematic flowchart of a method for acquiring picture sharpness provided by an embodiment of the present application.

FIG. 4 is a schematic diagram of a scenario for acquiring a picture sharpness according to an embodiment of the present application.

FIG. 6 is a schematic structural diagram of an apparatus for acquiring picture sharpness according to an embodiment of the present application.

FIG. 7 is another schematic structural diagram of an apparatus for acquiring picture sharpness according to an embodiment of the present application.

FIG. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

FIG. 9 is another schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed ways

Referring to the drawings, in which like reference numerals represent the same components, the principles of the present application are illustrated by way of example in a suitable computing environment. The following description is based on the specific embodiments of the present invention as illustrated, and should not be construed as limiting the specific embodiments that are not described herein.

The embodiment of the present application provides a method for acquiring picture sharpness, which includes:

Obtaining an original picture obtained by shooting according to a Bayer array; determining a target area from the original picture, and determining a distribution position of a pixel of a preset color from the target area; acquiring a distribution position relationship in the target area as a pair a square value of a difference value of luminance values of pixels of adjacent preset colors; summing the square values of all the difference values to obtain a sum value, and determining the sum value as the sharpness of the picture.

In an implementation manner, the obtaining a square value of a difference value of a brightness value of a pixel of a preset color in a diagonally adjacent positional relationship in the target area may include: determining, from the target area a target pixel having the same preset color pixel distribution at positions adjacent to the lower left diagonally adjacent to the lower right diagonal corner; obtaining a difference value of luminance values of each of the target pixels and pixels adjacent to the lower left diagonal thereof The squared value and obtain the square of the difference between the luminance value of each target pixel and the pixel adjacent to its lower right diagonal.

In an embodiment, the determining the target area from the original picture may include: determining a target area from the original picture, where the target area is a rectangular area of a preset size.

In an embodiment, the determining the target area from the original picture may include: determining a target area from the original picture, the target area being a required focus area.

In an embodiment, before the acquiring the original image obtained by the Bayer array, the method further includes: acquiring the total running memory capacity of the electronic device when the electronic device enters the shooting interface and needs to acquire the sharpness of the image. And the running memory capacity currently occupied; obtaining the percentage of the currently occupied running memory capacity as a percentage of the total running memory capacity.

Then, the acquiring the original image obtained by the Bayer array may include: if the percentage value is detected to be greater than the preset ratio threshold, acquiring the original image obtained by the Bayer array.

In an embodiment, the method for acquiring the image sharpness may further include: adjusting the preset ratio threshold.

In an embodiment, the adjusting the preset ratio threshold may include: acquiring a preset basic value; and increasing or decreasing the basic value according to the preset amplitude to obtain a preset proportional threshold.

It can be understood that the executive body of the embodiment of the present application may be an electronic device such as a smart phone or a tablet computer.

Referring to FIG. 1 , FIG. 1 is a schematic flowchart of a method for acquiring picture sharpness according to an embodiment of the present disclosure, where the process may include:

In 101, an original picture taken based on a Bayer array is acquired.

In the process of taking a picture, the electronic device needs to evaluate the picture obtained by the camera module. In the related art, the electronic device can perform a sharpness evaluation on a picture using a sharpness evaluation algorithm. For example, commonly used definition evaluation algorithms include Sobel operators and the like. However, when using these definition evaluation algorithms to obtain the sharpness of the picture, it is necessary to interpolate the original picture (Bayer Raw picture) obtained based on the Bayer array image, which results in low efficiency in obtaining picture sharpness.

In the 101 of the embodiment of the present application, for example, when it is necessary to acquire the resolution of the picture, the electronic device may first acquire an original picture (Bayer RAW picture) obtained based on the Bayer array.

It should be noted that the original picture taken based on the Bayer array image refers to the original picture inside the unprocessed camera captured by the camera module mounted with the Bayer array sensor.

In 102, a target area is determined from the original picture, and a distribution position of pixels of a preset color is determined from the target area.

For example, after acquiring the original picture taken based on the Bayer array, the electronic device can determine a target area from the original picture. The target area is an area for obtaining the sharpness of the original picture.

After determining the target area from the original picture taken by the Bayer array, the electronic device can determine the distribution position of the pixels of the preset color from the target area.

For example, the electronic device can determine the distribution location of the green pixels from the target area. Of course, the preset color can also be other colors, such as red or blue. It should be understood that the examples herein do not constitute a limitation on the embodiments of the present application.

In 103, a square value of a difference value of luminance values of pixels of a preset color in which the distribution position relationship in the target area is diagonally adjacent is acquired.

For example, after determining the distribution position of the green pixel from the target area, the electronic device may acquire the square value of the difference of the brightness value of each of the two green pixels adjacent to the diagonally adjacent positional relationship in the target area.

It should be noted that diagonally adjacent means that the relationship between two pixels in the distribution position is that the two pixels have a vertex angle.

As shown in FIG. 2, for example, the figure is a schematic diagram of pixel distribution of a target area in a Bayer RAW image. The pixels R00, R02, R20, and R22 are red pixels, G01, G03, G10, G12, G21, G23, G30, and G32 are green pixels, and B11, B13, B31, and B33 are blue pixels.

Then, for example, G01 and G10 are diagonally adjacent green pixels, G01 and G12 are diagonally adjacent green pixels, G12 and G21 are diagonally adjacent green pixels, and G12 and G23 are diagonally adjacent green pixels. Pixel. However, G01 and G23 are not diagonally adjacent green pixels, and G01 and G21 are not diagonally adjacent green pixels.

For example, for two diagonally adjacent green pixels, G01 and G10, the electronic device can obtain the squared value of the difference in their luminance values. For example, the green pixel of G01 has a luminance value of L01, and the green pixel of G10 has a luminance value of L10. Then, the electronic device can acquire R1=(L01-L10) ² . For the two diagonally adjacent green pixels G01 and G12, the electronic device can obtain the squared value of the difference of their luminance values. For example, the green pixel of G01 has a luminance value of L01, and the green pixel of G12 has a luminance value of L12. Then, the electronic device can acquire R2=(L01-L12) ² .

In 104, the square values of all the differences are added to obtain a sum value, and the sum value is determined as the sharpness of the picture.

For example, after obtaining the square value of the difference of the luminance values of all the diagonally adjacent green pixels, the electronic device can add the square values of all the differences to obtain a sum value. The electronic device can then determine the sum value as the sharpness of the picture.

It can be understood that, because the technical solution in the embodiment of the present application can directly obtain the definition on the basis of the original image obtained by the Bayer array, without first interpolating the original image obtained by the Bayer array shooting, Then obtain the definition. Therefore, the embodiment of the present application can improve the efficiency of obtaining picture clarity.

In addition, since the technical solution in the embodiment of the present application does not need to involve picture recognition, the scheme in this embodiment has high robustness and stability. Moreover, the scheme in this embodiment has a high acquisition accuracy.

Referring to FIG. 3, FIG. 3 is another schematic flowchart of a method for acquiring picture sharpness according to an embodiment of the present disclosure, where the process may include:

In 201, the electronic device acquires an original picture taken based on a Bayer array.

For example, when it is necessary to obtain the resolution of the picture, the electronic device can first obtain the original picture (Bayer RAW picture) obtained based on the Bayer array.

In 202, the electronic device determines a target area from the original picture, the target area being a rectangular area of a preset size.

For example, after acquiring the original picture taken based on the Bayer array, the electronic device can determine a target area from the original picture. The target area is an area for obtaining the sharpness of the original picture. The target area may be a rectangular area of a preset size.

In 203, the electronic device determines a distribution position of the pixels of the preset color from the target area.

For example, after the target area is determined from the original picture taken by the Bayer array, the electronic device can determine the distribution position of the pixels of the preset color from the target area.

In 204, the electronic device determines, from the target area, a target pixel having a pixel distribution of the same preset color at positions adjacent to the lower left diagonally adjacent to the lower right diagonal.

For example, after determining the distribution position of the green pixel from the target area, the electronic device may determine, from the target area, a target having a green pixel distribution at a position adjacent to the lower left diagonally adjacent to the lower right diagonal corner. Pixel. The color of the target pixel is also a preset color.

For example, FIG. 2 is a schematic diagram of pixel distribution of a target area of a certain picture. As shown in FIG. 2, the pixels R00, R02, R20, and R22 are red pixels, G01, G03, G10, G12, G21, G23, G30, and G32 are green pixels, and B11, B13, B31, and B33 are blue pixels.

For example, for the green pixel G01 in the figure, since the green pixel G10 is distributed at its lower left diagonal adjacent position, the green pixel G12 is distributed at its lower right diagonal adjacent position. Therefore, the electronic device can determine the green pixel G01 as the target pixel. Similarly, the electronic device can also determine the green pixels G12 and G21 as target pixels.

For the green pixel G03, since the green pixel G12 is distributed in the lower left diagonal position, the green pixel is not distributed in the lower right diagonal position. Therefore, the electronic device may not determine the green pixel G03 as the target pixel.

For another example, for the green pixel G10, since the green pixel G21 is distributed at the diagonally adjacent position in the lower right corner thereof, the green pixel is not distributed in the lower left diagonally adjacent position. Therefore, the electronic device may not determine the green pixel G10 as the target pixel.

Similarly, the electronic device may not determine the green pixels G23, G30, and G32 as the target pixels.

In 205, the electronic device acquires a square value of a difference value between each target pixel and a luminance value of a pixel adjacent to a lower left diagonal of the target pixel, and acquires each target pixel and a pixel adjacent to a diagonally lower right corner thereof. The square of the difference in luminance values.

For example, after determining the target pixel in the target area, the electronic device may acquire the square value of the difference between the brightness value of each target pixel and the same color pixel adjacent to the lower left diagonal of the target pixel, and acquire each target. The square of the difference between the pixel and the luminance value of the same color pixel that is adjacent to its lower right diagonal.

For example, for the green pixel G01, the electronic device may first obtain the square value of the difference between the luminance values of G01 and the green pixel G10 adjacent to the lower left diagonal. For example, the green pixel of G01 has a luminance value of L01, and the green pixel of G10 has a luminance value of L10. Then, the electronic device can acquire R1=(L01-L10) ² . Then, the electronic device can acquire the square value of the difference between the luminance values of G01 and the green pixel G12 adjacent to its lower right diagonal. For example, the green pixel of G12 has a luminance value of L12. Then, the electronic device can acquire R2=(L01-L12) ² .

For the green pixel G12, the electronic device may first obtain the square value of the difference between the luminance values of the green pixel G21 adjacent to the lower left diagonal of G12. For example, the green pixel of G12 has a luminance value of L12, and the green pixel of G21 has a luminance value of L21. Then, the electronic device can acquire R3=(L12-L21) ² . Then, the electronic device can acquire the square value of the difference between the luminance values of the green pixel G23 adjacent to the lower right corner of the G12. For example, the green pixel of G23 has a luminance value of L23. Then, the electronic device can acquire R4=(L12-L23) ² .

For the green pixel G21, the electronic device may first obtain the square value of the difference between the luminance values of the green pixel G30 adjacent to the lower left diagonal of G21. For example, the green pixel of G21 has a luminance value of L21, and the green pixel of G30 has a luminance value of L30. Then, the electronic device can acquire R5=(L21-L30) ² . Then, the electronic device can acquire the square value of the difference between the luminance values of the green pixel G32 adjacent to the lower right diagonal of G21. For example, the green pixel of G32 has a luminance value of L32. Then, the electronic device can acquire R6=(L21-L32) ² .

For the non-target pixels G03, G10, G23, G30, G32, the electronic device may not obtain the square value of the difference between the luminance values of the pixels and their lower left diagonal adjacent pixels or the lower right diagonal adjacent pixels.

In 206, the electronic device adds all the squared values of the difference to obtain a sum value, and determines the sum value as the sharpness of the picture.

For example, the square value of the difference between the luminance values of each of the target pixels and the pixels adjacent to the lower left diagonal of the target pixel, and the difference between the luminance values of the pixels adjacent to the lower right diagonal of the target pixel are obtained. After the square value, the electronic device can add the square values of all these differences to obtain a sum value. The electronic device can then determine the sum value as the sharpness of the picture.

For example, the electronic device may add the above R1, R2, R3, R4, R5, and R6 to obtain a sum value C. That is, C=R1+R2+R3+R4+R5+R6. The electronic device can then determine the sum value C as the sharpness of the original picture.

In an embodiment, the electronic device may also determine the sum value as the contrast of the original picture.

In an embodiment, the process in which the electronic device determines the target area from the original picture in 202 may include:

The electronic device determines a target area from the original picture, the target area being a desired focus area.

For example, after acquiring the original picture taken based on the Bayer array, the electronic device may determine the required focus area in the original picture as the target area.

It should be noted that the focus area needs to be the area with the highest resolution requirement in the original picture, so the required focus area can be determined as the target area for obtaining the sharpness of the original picture.

In an embodiment, before the electronic device acquires the original image captured by the Bayer array in 201, the following process may be further included:

When the electronic device enters the shooting interface and needs to obtain the sharpness of the picture, the electronic device acquires the total running memory capacity of the electronic device and the currently occupied running memory capacity;

The electronic device obtains the percentage of the currently occupied running memory capacity as a percentage of the total running memory capacity.

Then, the process of the electronic device in 201 acquiring the original image obtained by the Bayer array may include: if the percentage value is detected to be greater than the preset ratio threshold, the electronic device acquires the original image obtained by the Bayer array.

For example, when the user uses the camera of the electronic device to perform actual shooting, that is, when the electronic device enters the shooting interface and needs to obtain the sharpness of several frames before and after the shooting, to assist the camera module to find the best focus position, the electronic device can First, get the total running memory capacity of the electronic device, and the running memory capacity currently occupied.

Then, the electronic device can obtain the percentage of the currently occupied running memory capacity as a percentage of the total running memory capacity, and detect whether the percentage value is greater than a preset ratio threshold.

If the percentage value is detected to be less than or equal to the preset ratio threshold, then the current computing power of the electronic device can be considered to be strong, and the electronic device can perform other operations to complete the photo shooting. For example, at this point the electronic device can perform direct calculations based on hardware logic to find the best focus position.

If it is detected that the percentage value is greater than the preset ratio threshold, that is, the remaining running memory of the electronic device is insufficient, the current computing capability of the electronic device may be considered to be poor. In this case, in order to avoid the system being stuck due to insufficient running memory, the electronic device can acquire the original picture taken based on the Bayer array, and execute the processes in the embodiments 201 to 206, thereby assisting the camera module to find The best focus position.

It can be understood that the technical solution of the embodiment can improve the efficiency of the electronic device to obtain picture clarity. Therefore, in the case where the remaining memory is insufficient, by using the flow in the present embodiment 201 to 206, it is possible to speed up the determination of the optimum focus position by the electronic device.

In an embodiment, the value of the preset ratio threshold may be allowed to be adjusted. For example, the electronic device can first obtain hardware information such as the model of the processor. If it is determined according to the hardware information of the processor that the computing power of the processor is strong, the electronic device may increase the value of the preset ratio threshold by a certain amount. If it is determined that the computing power of the processor is poor according to the hardware information of the processor, the electronic device may lower the value of the preset ratio threshold. For example, the electronic device may set a basic value in advance, and when it is determined that the computing power of the processor is strong according to the hardware information of the processor, the electronic device may increase the basic value by a preset amplitude to obtain a preset proportional threshold. When it is determined that the computing power of the processor is poor according to the hardware information of the processor, the electronic device may reduce the base value by a preset amplitude to obtain a preset ratio threshold.

That is, in an embodiment, the embodiment may further include the following process: the electronic device adjusts the preset ratio threshold.

In an embodiment, when the electronic device performs the process of adjusting the preset ratio threshold, the electronic device may: the electronic device acquires a preset basic value; and the electronic device increases or decreases the basic value according to the preset amplitude to obtain the pre-prepared Set the proportional threshold.

In another embodiment, if the shooting mode of the camera of the electronic device includes a fast shooting mode, an automatic shooting mode, and a professional shooting mode, the technical solution provided in the embodiment of the present application may be used when the fast shooting mode is used, so that Increase the camera's focus speed for electronic devices. The quick shooting mode may be a shooting mode for capturing a picture of a dynamic object.

Referring to FIG. 4 to FIG. 5 , FIG. 4 to FIG. 5 are schematic diagrams of a method for acquiring a picture sharpness according to an embodiment of the present application.

In the production process of the camera module, it is necessary to perform a shooting test on the camera module. Among them, the camera module needs to evaluate the resolution of several frames before and after the shooting, and determines the best focus position according to the resolution of the photos, so as to shoot the highest resolution photos. . For example, in the process of driving the lens from the first position to the second position, the sharpness of the original picture (Bayer RAW picture) or preview image captured by the camera is continuously increased, and the lens is driven from the second position to the first position. During the three-position process, the sharpness of the original or preview image captured by the camera is continuously reduced. Then, the electronic device can determine the second position as the best focus position and drive the lens to the second position to complete the shooting.

For example, when the production of the camera module is tested and the focus is on, the electronic device can first obtain the original image taken based on the Bayer array. It should be noted that the original picture taken based on the Bayer array image refers to the original picture inside the unprocessed camera captured by the camera module mounted with the Bayer array sensor. For example, when the lens is driven to the first position, the electronic device may first acquire the first original picture obtained based on the Bayer array.

Then, the electronic device can determine a target area from the first original picture. The target area may be a rectangular area that requires a focus area, and the target area is a preset size. For example, as shown in FIG. 4, when the user clicks on the camera to capture the face area in the preview interface and wants to focus on the face, the face area needs to be the focus area (the dotted area in the figure indicates the face area that needs to be focused). . Therefore, the electronic device can determine the face area as the target area, and the target area can be a rectangular area of a preset size.

Thereafter, the electronic device may determine a distribution position of the green pixel from the target area, and determine, from the target area, a target pixel having a green pixel distribution at a position adjacent to a lower left diagonally opposite and a lower right diagonal opposite .

For example, FIG. 2 is a pixel distribution diagram of a target area determined from the first original picture. As shown in FIG. 2, for the green pixel G01 in the figure, since the green pixel G10 is distributed at the lower left diagonally adjacent position, the green pixel G12 is distributed at the lower right diagonally adjacent position. Therefore, the electronic device can determine the green pixel G01 as the target pixel. Similarly, the electronic device can also determine the green pixels G12 and G21 as target pixels.

After determining the target pixel in the target area, the electronic device may acquire a square value of a difference value of each target pixel and a luminance value of a pixel adjacent to a lower left diagonal of the target pixel, and acquire each target pixel and distribution The square of the difference in luminance values of pixels adjacent to the lower right diagonal.

Thereafter, the electronic device can add R1, R2, R3, R4, R5, and R6 to obtain a sum value C. That is, C=R1+R2+R3+R4+R5+R6. After obtaining the sum value C, the electronic device can determine the sum value C as the sharpness of the first original picture.

Similarly, after the lens is driven to the second position, for example, the electronic device acquires the resolution of the second original picture corresponding to the second position to be D. After driving the lens to the third position, the electronic device acquires the resolution of the third original picture corresponding to the third position to be E.

For example, if the electronic device detects that C is less than D and D is greater than E in the sharpness value, the electronic device can determine the second position as the best focus position and drive the lens to the second position to complete the photo shooting.

For example, after driving the lens to the second position, the electronic device can prompt the tester to complete the focus (in the figure, the dotted frame of the face area is changed to a solid line frame to indicate that the focus is completed). After the user gets the prompt, press the camera button, as shown in FIG. 5, to complete the photo shooting.

The embodiment of the present application provides a device for acquiring picture sharpness, which includes:

The first obtaining module is configured to obtain an original picture obtained by shooting according to a Bayer array.

a first determining module, configured to determine a target area from the original picture, and determine a distribution position of pixels of a preset color from the target area.

And a second acquiring module, configured to acquire a square value of a difference value of a luminance value of a pixel of a preset color in which the distribution position relationship in the target area is diagonally adjacent.

In an embodiment, the second obtaining module may be configured to: determine, from the target area, a pixel distribution having the same preset color in a position adjacent to a lower left diagonal and a lower right diagonal opposite a target pixel; obtaining a square value of a difference value between each target pixel and a luminance value of a pixel adjacent to a lower left diagonal of the target pixel, and acquiring a luminance value of each target pixel and a pixel adjacent to a diagonally lower diagonal corner thereof The squared value of the difference.

In an embodiment, the first determining module may be configured to: determine a target area from the original picture, where the target area is a rectangular area of a preset size.

In an embodiment, the first determining module may be configured to: determine a target area from the original picture, where the target area is a required focus area.

In an embodiment, the image clarity acquiring device may further include: a third acquiring module, configured to acquire a total running memory of the electronic device when the electronic device enters the shooting interface and needs to acquire the sharpness of the image The capacity and the currently occupied running memory capacity; obtaining the percentage of the currently occupied running memory capacity as a percentage of the total running memory capacity.

Then, the first acquiring module may be configured to: if the percentage value is detected to be greater than a preset ratio threshold, obtain an original picture obtained by shooting according to a Bayer array.

In an implementation manner, the third acquiring module may be further configured to: adjust the preset ratio threshold.

In an embodiment, the third obtaining module may be further configured to: obtain a preset basic value; and increase or decrease the basic value according to a preset amplitude to obtain a preset proportional threshold.

Please refer to FIG. 6. FIG. 6 is a schematic structural diagram of an apparatus for acquiring picture sharpness according to an embodiment of the present disclosure. The image sharpness obtaining apparatus 300 may include: a first obtaining module 301, a first determining module 302, a second obtaining module 303, and a second determining module 304.

The first obtaining module 301 is configured to acquire an original picture obtained by shooting according to a Bayer array.

For example, when it is necessary to obtain the resolution of the picture, the first obtaining module 301 may first acquire an original picture (Bayer RAW picture) obtained based on the Bayer array.

The first determining module 302 is configured to determine a target area from the original picture, and determine a distribution position of pixels of a preset color from the target area.

For example, after the first obtaining module 301 obtains the original image captured by the Bayer array, the first determining module 302 may determine a target area from the original image. The target area is an area for obtaining the sharpness of the original picture.

After determining the target area from the original picture taken by the Bayer array, the first determining module 302 may determine the distribution position of the pixels of the preset color from the target area.

For example, the first determining module 302 can determine a distribution location of the green pixels from the target area. Of course, the preset color can also be other colors, such as red or blue. It should be understood that the examples herein do not constitute a limitation on the embodiments of the present application.

The second obtaining module 303 is configured to acquire a square value of a difference value of the luminance values of the pixels of the preset color in the target area.

For example, after the first determining module 302 determines the distribution position of the green pixel from the target area, the second obtaining module 303 may obtain the brightness value of each of the two green pixels adjacent to the diagonally distributed positional relationship in the target area. The squared value of the difference.

For example, for the two diagonally adjacent green pixels G01 and G10, the second acquisition module 303 can obtain the square value of the difference of their luminance values. For example, the green pixel of G01 has a luminance value of L01, and the green pixel of G10 has a luminance value of L10. Then, the second obtaining module 303 can acquire R1=(L01-L10) ² . For the two diagonally adjacent green pixels G01 and G12, the second acquisition module 303 can obtain the squared value of the difference of their luminance values. For example, the green pixel of G01 has a luminance value of L01, and the green pixel of G12 has a luminance value of L12. Then, the electronic device can acquire R2=(L01-L12) ² .

The second determining module 304 is configured to add the square values of all the difference values to obtain a sum value, and determine the sum value as the sharpness of the picture.

For example, after the second obtaining module 303 obtains the square value of the difference value of the luminance values of all the diagonally adjacent green pixels, the second determining module 304 may add the square values of all the difference values to obtain a sum. value. The second determination module 304 can then determine the sum value as the sharpness of the picture.

In an embodiment, the second obtaining module 303 can be used to:

Determining, from the target area, a target pixel having a pixel distribution of the same preset color at positions adjacent to the lower left diagonally adjacent to the lower right diagonal corner;

Obtaining a square value of a difference value between each target pixel and a luminance value of a pixel adjacent to a lower left diagonal thereof, and obtaining a difference value of each target pixel and a luminance value of a pixel adjacent to a lower right diagonal corner thereof The squared value.

For example, after determining the distribution position of the green pixel from the target area, the second obtaining module 303 may determine, from the target area, that there are green pixels in the position adjacent to the lower left diagonal and the lower right diagonal. The target pixel of the distribution.

For example, for the green pixel G01 in the figure, since the green pixel G10 is distributed at its lower left diagonal adjacent position, the green pixel G12 is distributed at its lower right diagonal adjacent position. Therefore, the second acquisition module 303 can determine the green pixel G01 as the target pixel. Similarly, the second acquisition module 303 can also determine the green pixels G12 and G21 as target pixels.

After determining the target pixel in the target area, the second obtaining module 303 may obtain a square value of a difference value between each target pixel and a luminance value of a same color pixel adjacent to a lower left diagonal of the target pixel, and acquire each The square of the difference between the target pixel and the luminance value of the same color pixel that is adjacent to its lower right diagonal.

For example, for the green pixel G01, the second acquisition module 303 may first obtain the square value of the difference between the luminance values of the green pixel G10 adjacent to the lower left diagonal of G01. For example, the green pixel of G01 has a luminance value of L01, and the green pixel of G10 has a luminance value of L10. Then, the second obtaining module 303 can acquire R1=(L01-L10) ² . Then, the second acquisition module 303 can acquire the square value of the difference between the luminance values of the green pixel G12 adjacent to the lower right diagonal of G01. For example, the green pixel of G12 has a luminance value of L12. Then, the second obtaining module 303 can acquire R2=(L01-L12) ² .

For the green pixel G12, the second acquisition module 303 may first obtain the square value of the difference between the luminance values of the green pixel G21 adjacent to the lower left diagonal of G12. For example, the green pixel of G12 has a luminance value of L12, and the green pixel of G21 has a luminance value of L21. Then, the second obtaining module 303 can acquire R3=(L12-L21) ² . Then, the second acquisition module 303 can acquire the square value of the difference between the luminance values of the green pixel G23 adjacent to the lower right diagonal of G12. For example, the green pixel of G23 has a luminance value of L23. Then, the second obtaining module 303 can acquire R4=(L12-L23) ² .

For the green pixel G21, the second acquisition module 303 may first obtain the square value of the difference between the luminance values of the green pixel G30 adjacent to the lower left diagonal of G21. For example, the green pixel of G21 has a luminance value of L21, and the green pixel of G30 has a luminance value of L30. Then, the second obtaining module 303 can acquire R5=(L21-L30) ² . Then, the second acquisition module 303 can acquire the square value of the difference between the luminance values of the green pixel G32 adjacent to the lower right diagonal of G21. For example, the green pixel of G32 has a luminance value of L32. Then, the second obtaining module 303 can acquire R6=(L21-L32) ² .

Thereafter, the second determining module 304 may add R1, R2, R3, R4, R5, R6 to obtain a sum value C, and determine the sum value C as the sharpness of the first original picture.

In an embodiment, the first determining module 302 can be used to:

A target area is determined from the original picture, the target area being a rectangular area of a preset size.

For example, after acquiring the original picture taken based on the Bayer array, the first determining module 302 can determine a target area from the original picture. The target area is an area for obtaining the sharpness of the original picture. The target area may be a rectangular area of a preset size.

In an embodiment, the first determining module 302 can be used to:

A target area is determined from the original picture, the target area being a desired focus area.

For example, after acquiring the original picture taken based on the Bayer array, the first determining module 302 may determine the required focus area in the original picture as the target area.

Please refer to FIG. 7 . FIG. 7 is another schematic structural diagram of an apparatus for acquiring picture sharpness according to an embodiment of the present application. In an embodiment, the image sharpness obtaining apparatus 300 may further include: a third obtaining module 305.

The third obtaining module 305 is configured to acquire the total running memory capacity of the electronic device and the currently occupied running memory capacity when the electronic device enters the shooting interface and needs to acquire the sharpness of the image; and acquire the currently occupied running The amount of memory capacity as a percentage of the total capacity of the running memory.

Then, the first obtaining module 301 can be configured to: if the percentage value is detected to be greater than a preset ratio threshold, obtain an original picture that is obtained based on a Bayer array.

For example, when the user uses the electronic device camera to perform actual shooting, that is, when the electronic device enters the shooting interface and needs to obtain the sharpness of several frames before and after the shooting, to assist the camera module to find the best focus position, the third acquiring module The 305 can first obtain the total running memory capacity of the electronic device and the currently occupied running memory capacity.

Then, the third obtaining module 305 can obtain the percentage value of the currently occupied running memory capacity as a percentage of the total running memory capacity, and detect whether the percentage value is greater than a preset ratio threshold.

If it is detected that the percentage value is greater than the preset ratio threshold, that is, the remaining running memory of the electronic device is insufficient, the current computing capability of the electronic device may be considered to be poor. In this case, in order to avoid the system being stuck due to insufficient running memory, the first acquiring module 301 of the electronic device can acquire the original picture taken based on the Bayer array and perform subsequent steps, thereby assisting the camera module to find the most Good focus position.

The embodiment of the present application provides a computer readable storage medium, where a computer program is stored thereon, and when the computer program is executed on a computer, the computer is caused to execute the image sharpness obtaining method provided by the embodiment. A step of.

The embodiment of the present application further provides an electronic device, including a memory, and a processor, by using a computer program stored in the memory, to execute the process in the method for acquiring picture sharpness provided by the embodiment.

Please refer to FIG. 8. FIG. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

The electronic device 400 can include components such as an imaging unit 401, a memory 402, a processor 403, and the like. It will be understood by those skilled in the art that the structure of the electronic device shown in FIG. 8 does not constitute a limitation on the electronic device, and may include more or less components than those illustrated, or combine some components, or different component arrangements. .

The camera unit 401 can be used to capture an image.

Memory 402 can be used to store applications and data. The application stored in the memory 402 contains executable code. Applications can form various functional modules. The processor 403 executes various functional applications and data processing by running an application stored in the memory 402.

The processor 403 is a control center of the electronic device, connects various parts of the entire electronic device using various interfaces and lines, executes the electronic device by running or executing an application stored in the memory 402, and calling data stored in the memory 402. The various functions and processing of data to provide overall monitoring of the electronic device.

In this embodiment, the processor 403 in the electronic device loads the executable code corresponding to the process of one or more applications into the memory 402 according to the following instructions, and is executed by the processor 403 to be stored in the memory. The application in 402, thus executing:

Referring to FIG. 9, the electronic device 500 may include components such as an imaging unit 501, a memory 502, a processor 503, an input unit 504, an output unit 505, and the like.

The imaging unit 501 can be used to capture an image.

Memory 502 can be used to store applications and data. The application stored in the memory 502 contains executable code. Applications can form various functional modules. The processor 503 executes various functional applications and data processing by running an application stored in the memory 502.

The processor 503 is a control center of the electronic device, and connects various parts of the entire electronic device using various interfaces and lines, executes the electronic device by running or executing an application stored in the memory 502, and calling data stored in the memory 502. The various functions and processing of data to provide overall monitoring of the electronic device.

The input unit 504 can be configured to receive input digits, character information or user characteristic information (such as fingerprints), and to generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function controls.

The output unit 505 can be used to display information input by the user or information provided to the user as well as various graphical user interfaces of the electronic device, which can be composed of graphics, text, icons, video, and any combination thereof. The output unit may include a display panel.

In this embodiment, the processor 503 in the electronic device loads the executable code corresponding to the process of one or more applications into the memory 502 according to the following instructions, and is stored in the memory by the processor 503. The application in 502, thus executing:

In an embodiment, when the processor 503 performs the acquiring a square value of a difference value of a luminance value of a pixel of a preset color in a diagonally adjacent positional relationship in the target area, the processor 503 may perform: from the Determining, in the target area, a target pixel having a pixel distribution of the same preset color at positions adjacent to the lower left diagonal and adjacent to the lower right diagonal; acquiring each target pixel and a pixel adjacent to the lower left diagonal of the target pixel The square value of the difference of the luminance values, and the square value of the difference between the luminance values of each of the target pixels and the pixels adjacent to the lower right diagonal of the target pixel is obtained.

In an embodiment, when the processor 503 performs the determining of the target area from the original picture, performing: determining, from the original picture, a target area, where the target area is a rectangular area of a preset size. .

In an embodiment, when the processor 503 performs the determining of the target area from the original picture, it may be performed to: determine a target area from the original picture, where the target area is a required focus area.

In an implementation manner, before performing the acquiring the original image obtained by the Bayer array, the processor 503 may further perform: acquiring, when the electronic device enters the shooting interface and needs to acquire the sharpness of the image, acquiring the electronic device. Running the total memory capacity and the currently occupied running memory capacity; obtaining the percentage of the currently occupied running memory capacity as a percentage of the total running memory capacity.

Then, when the processor 503 performs the acquiring the original image obtained by the Bayer array, the processor 503 may perform: if the percentage value is greater than the preset ratio threshold, the original image obtained by the Bayer array is acquired.

In an embodiment, the processor 503 may further perform: adjusting the preset ratio threshold.

In an embodiment, when the processor 503 performs the adjustment on the preset ratio threshold, the method may: perform: acquiring a preset basic value; and increasing or decreasing the basic value according to the preset amplitude to obtain a preset. Proportional threshold.

In the above-mentioned embodiments, the descriptions of the various embodiments are all focused. For a part that is not detailed in a certain embodiment, reference may be made to the above detailed description of the method for obtaining picture sharpness, and details are not described herein again.

The image sharpness obtaining device provided by the embodiment of the present application belongs to the same concept as the image sharpness obtaining method in the above embodiment, and the image sharpness acquisition can be performed on the image sharpness obtaining device. For the specific implementation process of any of the methods provided in the method embodiments, refer to the embodiment of the method for obtaining the picture clarity, which is not described here.

It should be noted that, in the method for obtaining the picture clarity according to the embodiment of the present application, a person skilled in the art may understand all or part of the process for implementing the picture clarity method according to the embodiment of the present application, which may be through a computer. The program is implemented by controlling related hardware, which may be stored in a computer readable storage medium, such as in a memory, and executed by at least one processor, and may include, as the picture is clear during execution The flow of an embodiment of the method of obtaining degrees. The storage medium may be a magnetic disk, an optical disk, a read only memory (ROM), a random access memory (RAM), or the like.

For the image sharpness obtaining device of the embodiment of the present application, each functional module may be integrated into one processing chip, or each module may exist separately physically, or two or more modules may be integrated into one module. in. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. The integrated module, if implemented in the form of a software functional module and sold or used as a standalone product, may also be stored in a computer readable storage medium, such as a read only memory, a magnetic disk or an optical disk, etc. .

The method, the device, the storage medium, and the electronic device for acquiring image sharpness provided by the embodiments of the present application are described in detail. The principles and implementation manners of the present application are described in the following. The descriptions are only used to help understand the method of the present application and its core ideas; at the same time, for those skilled in the art, according to the idea of the present application, there will be changes in the specific embodiments and application scopes. The contents of this specification are not to be construed as limiting the application.

Claims

A method for obtaining image sharpness, including:

Obtaining the original image taken based on the Bayer array;

Determining a target area from the original picture, and determining a distribution position of pixels of a preset color from the target area;

Obtaining a square value of a difference value of a luminance value of a pixel of a preset color in a diagonally adjacent preset color position in the target area;

The sum of the squared values of all the differences is obtained to obtain a sum value, and the sum value is determined as the sharpness of the picture.
The method for acquiring picture sharpness according to claim 1, wherein the obtaining a square value of a difference value of a brightness value of a pixel of a preset color in a diagonally adjacent positional relationship in the target area includes:

Determining, from the target area, a target pixel having a pixel distribution of the same preset color at positions adjacent to the lower left diagonally adjacent to the lower right diagonal corner;

Obtaining a square value of a difference value between each target pixel and a luminance value of a pixel adjacent to a lower left diagonal thereof, and obtaining a difference value of each target pixel and a luminance value of a pixel adjacent to a lower right diagonal corner thereof The squared value.
The method for acquiring picture sharpness according to claim 2, wherein the determining the target area from the original picture comprises:

A target area is determined from the original picture, the target area being a rectangular area of a preset size.
The method for acquiring picture sharpness according to claim 3, wherein the determining the target area from the original picture comprises:

A target area is determined from the original picture, the target area being a desired focus area.
The method for acquiring picture sharpness according to claim 4, further comprising: before the acquiring the original picture taken based on the Bayer array image,

Obtaining a total operating memory capacity of the electronic device and a currently occupied operating memory capacity when the electronic device enters the shooting interface and needs to obtain the sharpness of the image;

Obtaining a percentage value of the currently occupied running memory capacity as a percentage of the total running memory capacity;

The acquiring the original image obtained by the Bayer array image comprises: if the percentage value is detected to be greater than the preset ratio threshold, acquiring the original image obtained by the Bayer array.
The method for obtaining picture sharpness according to claim 5, wherein the method further comprises:

Adjusting the preset ratio threshold.
The method for acquiring picture sharpness according to claim 6, wherein the adjusting the preset ratio threshold comprises:

Obtain a preset base value;

The base value is increased or decreased according to a preset amplitude to obtain a preset ratio threshold.
A device for acquiring picture sharpness, comprising:

a first acquiring module, configured to acquire an original picture obtained by shooting according to a Bayer array;

a first determining module, configured to determine a target area from the original picture, and determine a distribution position of a pixel of a preset color from the target area;

a second acquiring module, configured to acquire a square value of a difference value of a luminance value of a pixel of a preset color in which the distribution position relationship in the target area is diagonally adjacent;

And a second determining module, configured to add the square values of all the difference values to obtain a sum value, and determine the sum value as the sharpness of the picture.
The apparatus for acquiring picture sharpness according to claim 8, wherein the second obtaining module is configured to:

Determining, from the target area, a target pixel having a pixel distribution of the same preset color at positions adjacent to the lower left diagonally adjacent to the lower right diagonal corner;

Obtaining a square value of a difference value between each target pixel and a luminance value of a pixel adjacent to a lower left diagonal thereof, and obtaining a difference value of each target pixel and a luminance value of a pixel adjacent to a lower right diagonal corner thereof The squared value.
The apparatus for acquiring picture sharpness according to claim 9, wherein the first determining module is configured to:

A target area is determined from the original picture, the target area being a rectangular area of a preset size.
The apparatus for acquiring picture sharpness according to claim 10, wherein the first determining module is configured to:

A target area is determined from the original picture, the target area being a desired focus area.
The device for acquiring picture sharpness according to claim 11, wherein the device further comprises: a third obtaining module, configured to acquire the electronic device when the electronic device enters the shooting interface and needs to acquire the sharpness of the image Running the total memory capacity and the currently occupied running memory capacity; obtaining the percentage of the currently occupied running memory capacity as a percentage of the total running memory capacity;

The first acquiring module is configured to: if the percentage value is detected to be greater than a preset ratio threshold, obtain an original picture obtained by shooting according to a Bayer array.
A storage medium having stored thereon a computer program, wherein when the computer program is executed on a computer, the computer is caused to perform the method of any one of claims 1 to 7.
An electronic device comprising a memory, a processor, wherein the processor is configured to execute by calling a computer program stored in the memory:

Obtaining the original image taken based on the Bayer array;

Determining a target area from the original picture, and determining a distribution position of pixels of a preset color from the target area;

Obtaining a square value of a difference value of a luminance value of a pixel of a preset color in a diagonally adjacent preset color position in the target area;

The sum of the squared values of all the differences is obtained to obtain a sum value, and the sum value is determined as the sharpness of the picture.
The electronic device of claim 14, wherein the processor is operative to:

Determining, from the target area, a target pixel having a pixel distribution of the same preset color at positions adjacent to the lower left diagonal and adjacent to the lower right diagonal;

Obtaining a square value of a difference value between each target pixel and a luminance value of a pixel adjacent to a lower left diagonal thereof, and obtaining a difference value of each target pixel and a luminance value of a pixel adjacent to a lower right diagonal corner thereof The squared value.
The electronic device of claim 15 wherein said processor is operative to:

A target area is determined from the original picture, the target area being a rectangular area of a preset size.
The electronic device of claim 16 wherein said processor is operative to:

A target area is determined from the original picture, the target area being a desired focus area.
The electronic device of claim 17 wherein said processor is operative to:

Obtaining a total operating memory capacity of the electronic device and a currently occupied operating memory capacity when the electronic device enters the shooting interface and needs to obtain the sharpness of the image;

Obtaining a percentage value of the currently occupied running memory capacity as a percentage of the total running memory capacity;

If it is detected that the percentage value is greater than the preset ratio threshold, the original picture obtained based on the Bayer array is acquired.
The electronic device of claim 18, wherein the processor is operative to:

Adjusting the preset ratio threshold.
The electronic device of claim 19, wherein the processor is operative to:

Obtain a preset base value;

The base value is increased or decreased according to a preset amplitude to obtain a preset ratio threshold.