WO2018187917A1

WO2018187917A1 - Method and device for assessing picture quality

Info

Publication number: WO2018187917A1
Application number: PCT/CN2017/079975
Authority: WO
Inventors: 谢俊
Original assignee: 深圳市柔宇科技有限公司
Priority date: 2017-04-10
Filing date: 2017-04-10
Publication date: 2018-10-18
Also published as: CN108475430A; CN108475430B

Abstract

A method and device for assessing picture quality. The method comprises: acquiring a first picture (S101); performing preprocessing on the first picture so as to obtain a preprocessed picture (S102); performing edge detection on the preprocessed picture so as to count the number N of edge points, N being a positive integer (S103); and when N is greater than or equal to a first threshold, using the first picture for determining the type of a target video file (S104). The method improves the efficiency of video format recognition.

Description

Picture quality evaluation method and device

Technical field

The present invention relates to the field of image processing, and in particular, to a picture quality evaluation method and apparatus.

Background technique

In recent years, with the development of Virtual Reality (VR) technology, and widely used in the playback of 360-degree video files and 3D video files, it has enriched people's entertainment life.

Video files in formats such as 360-degree video files and 3D video files do not have a uniform file identifier. Many players recognize whether the video file is in a 360-degree video format or a 3D video format by intercepting a picture frame in the video file. However, in the process of intercepting the picture frame, sometimes the picture with the solid color, the large area solid color or the low contrast is intercepted. This picture is not suitable as the basis for identifying the video type, and the picture frame needs to be re-interpreted after the recognition calculation. Recognizing again, resulting in a reduction in the efficiency of video format recognition.

Summary of the invention

The embodiment of the invention discloses a picture quality evaluation method and device, which improves the efficiency of video format recognition.

In a first aspect, an embodiment of the present invention discloses a picture quality evaluation method, including:

Get the first picture;

Performing pre-processing on the first picture to obtain a pre-processed picture;

Performing edge detection on the preprocessed picture to count the number N of edge points, where N is a positive integer;

The first picture is used to determine a target video file type when the N is greater than or equal to a first threshold.

In a second aspect, an embodiment of the present invention discloses a picture quality evaluation apparatus, including:

a first acquiring module, configured to acquire a first picture;

a processing module, configured to perform pre-processing on the first picture to obtain a pre-processed picture;

a detecting module, configured to perform edge detection on the preprocessed picture to count the number N of edge points, The N is a positive integer;

And a determining module, configured to use the first picture to determine a target video file type when the N is greater than or equal to the first threshold.

In a third aspect, an embodiment of the present invention discloses a picture quality evaluation apparatus, including:

a memory storing executable program code;

a processor coupled to the memory;

The processor invokes the executable program code stored in the memory to perform all or part of the steps of the first aspect.

It can be seen that, in the solution of the embodiment of the present invention, first, the first picture is obtained from the video file; secondly, the first picture is preprocessed to obtain a preprocessed picture; and again, the preprocessed picture is performed. Edge detection, to count the number N of edge points, the N is a positive integer; when the N is greater than or equal to the first threshold, the first picture is used to determine the target video file type. Compared with the prior art, the solution of the embodiment of the invention improves the efficiency of video format recognition.

DRAWINGS

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings to be used in the embodiments will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the present invention. Those skilled in the art can also obtain other drawings based on these drawings without paying any creative work.

1 is a schematic flowchart of a picture quality evaluation method according to an embodiment of the present invention;

2 is a schematic diagram of pixel points of a picture;

3 is a schematic diagram of another picture pixel point;

FIG. 4 is a schematic flowchart diagram of another picture quality evaluation method according to an embodiment of the present disclosure;

FIG. 5 is a schematic structural diagram of a picture quality evaluation method according to an embodiment of the present invention;

FIG. 6 is a schematic structural diagram showing a partial structure of a picture quality evaluation method according to an embodiment of the present disclosure;

FIG. 7 is a schematic partial structural diagram of a picture quality evaluation method according to an embodiment of the present invention;

FIG. 8 is a schematic structural diagram of another picture quality evaluation method according to an embodiment of the present invention.

detailed description

The technical solutions in the embodiments of the present invention are clearly and completely described in the following with reference to the accompanying drawings in the embodiments of the present invention. It is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts are within the scope of the present invention.

Please refer to FIG. 1. FIG. 1 is a schematic flowchart diagram of an image quality evaluation method according to an embodiment of the present invention. As shown in Figure 1, the method includes:

S101. The picture quality evaluation apparatus acquires the first picture.

The first picture is a frame picture in the target video file. The target video file is a video file of a type to be determined.

Optionally, the target video file may be a VR video file, a 3D video file, a 360-degree video file, or other video files.

Further, the first picture is a key frame in the target video file. The key frame is the frame in which the key action in the motion or change of the character or object in the target video file is located.

S102. The picture quality evaluation apparatus performs preprocessing on the first picture to obtain a preprocessed picture.

The pre-processing the first picture to obtain a pre-processed picture includes:

Performing resolution processing on the first picture to obtain a second picture;

Performing grayscale processing on the second picture to obtain a third picture;

Performing a histogram equalization process on the third picture to obtain a preprocessed picture.

Specifically, performing the resolution processing on the first picture by the picture quality evaluation apparatus is specifically: reducing the resolution of the first picture to a preset value, and using the reduced first picture as the second picture.

Optionally, the preset value may be 640x480, 320x180, 567x390, 626x413 or other values. Preferably, the above preset value is 320x180.

Specifically, the picture quality evaluation apparatus performs grayscale processing on the second picture, in particular, converting the second picture from a color picture to a gray picture, and using the gray picture as the third picture.

The above image quality evaluation apparatus performs histogram equalization processing on the third picture to make The third picture described above changes faster, avoiding that the third picture is a gradation picture and no edge is detected.

S103. The picture quality evaluation apparatus performs edge detection on the preprocessed picture to count the number N of edge points, where N is a positive integer.

The performing edge detection on the preprocessed picture to count the number N of edge points includes:

Edge detection is performed on M pixel points in the preset area of the preprocessed picture to obtain M detection values, and the M detection values are in one-to-one correspondence with the M pixel points;

A pixel point corresponding to the second threshold value of the M detection values is used as an edge point to count the number N of edge points, and the M is greater than or equal to N.

For example, the preset area mentioned above is referred to FIG. 2, and FIG. 2 is a schematic diagram of pixel points of a preprocessed picture. The black point is the pixel of the preprocessed picture. In FIG. 2, there are n columns of pixels on the horizontal axis and m rows of pixels on the vertical axis, and the size of the preprocessed picture may be mxn. The preset region from the m-th row may be between ₁ to ₂ m-th row region in FIG. 2, FIG. 2 may also be in the region from the first column to the n ₁ n ₂ between the second column, may also FIG. 2 in between the m-th row to the m-th row ₁ and column ₂ intersection region between n ₁ to n ₂ of the second column.

Wherein, the above m _{1 is} greater than or equal to 0 and less than or equal to m-2, and the above m _{2 is} greater than or equal to 1 and less than or equal to m-1. The above n _{1 is} greater than or equal to 0 and less than or equal to n-2, and the above n _{2 is} greater than or equal to 1 and less than or equal to n-1.

The magnitudes of the above m ₁ , m ₂ , n ₁ , and n ₂ may be set according to the size of the preprocessed picture.

Referring to FIG. 3, assuming that the size of the preprocessed picture is 320x180, the preset area is the area between the 45th line and the 274th line in FIG. 3, that is, the 45th line and the last number in the picture shown in FIG. The area between 45 lines.

After determining the preset area, the picture quality evaluation apparatus obtains the detection values one by one for the M pixel points in the preset area to obtain M detection values. The image quality evaluation apparatus then compares the M detection values one by one with the second threshold. If the detected value A is greater than the second threshold, the pixel corresponding to the detected value A is taken as an edge point. The detected value A is any one of the M detection values. Finally, the picture quality evaluation device counts the number of edge points to obtain the number N of edge points.

Optionally, performing edge detection on M pixel points in a preset area of the preprocessed picture Testing, including:

Edge detection is performed on M pixel points in a preset area of the preprocessed picture by a detection operator.

Optionally, the above image quality evaluation device may also pass a Prewitt operator, a Canny operator, a Roberts operator, a Sobel operator, and Krisch. An operator or other operator performs edge detection on M pixels in the preset area of the preprocessed picture.

S104. When the N is greater than or equal to the first threshold, the picture quality evaluation apparatus uses the first picture to determine a target video file type.

Optionally, when the N is less than the first threshold, the method includes:

Obtaining a fourth picture, where the fourth picture is a frame picture different from the first picture in the target video file;

Performing a picture quality evaluation operation based on the fourth picture.

Specifically, after the picture quality evaluation device acquires the number N of edge points of the preprocessed picture, it is determined whether the N is greater than or equal to the first threshold. If it is determined that the N is greater than or equal to the first threshold, the picture quality evaluation apparatus may use the first picture corresponding to the pre-processed picture to confirm the type of the target video file. If it is determined that the above N is smaller than the first threshold, the picture quality evaluation apparatus acquires the fourth picture, and performs the processes described in the above steps S102-S104 again. The fourth picture is a frame picture different from the first picture in the target video file, and the fourth picture is a key frame in the target video file.

The value of the first threshold is determined according to the size of the preprocessed picture.

Optionally, the first threshold may be 1280 or other values.

Referring to FIG. 4, FIG. 4 is a flowchart showing another method for evaluating picture quality according to an embodiment of the present invention. intention. As shown in FIG. 4, the method includes:

S401. The picture quality evaluation apparatus acquires the first picture.

S402. The picture quality evaluation apparatus performs resolution processing on the first picture to obtain a second picture.

S403. The second picture of the picture quality evaluation apparatus performs grayscale processing to obtain a third picture.

S404. The third picture of the picture quality evaluation apparatus performs histogram equalization processing to obtain a preprocessed picture.

S405. The picture quality evaluation apparatus performs edge detection on the M pixel points in the preset area of the preprocessed picture, and acquires M detection values.

S406. The picture quality evaluation apparatus determines whether the M pixel points are edge points one by one, and counts the number N of edge points.

S407. The picture quality evaluation apparatus determines whether the N is greater than or equal to a first threshold.

If it is determined that the N is greater than or equal to the first threshold, the picture quality evaluation apparatus performs step S408; otherwise, the picture quality evaluation apparatus performs step S409.

S408. The picture quality evaluation apparatus uses the first picture to determine a type of the target video file.

S409. The picture quality evaluation apparatus acquires a fourth picture, and performs the above steps S402-S407 again.

It should be noted that the description of the above steps S401-S409 can be referred to the related description of the above steps S101-S104, and will not be described here.

Referring to FIG. 5, FIG. 5 is a schematic structural diagram of a picture quality evaluation apparatus according to an embodiment of the present invention. As shown in FIG. 5, the apparatus 500 includes:

The first obtaining module 501 is configured to acquire a first picture.

Optionally, the first picture is a frame of pictures in the target video file.

Optionally, the first picture is a key frame in the target video file.

The processing module 502 is configured to perform pre-processing on the first picture to obtain a pre-processed picture.

Optionally, the processing module 502 includes:

The first processing unit 5021 is configured to perform resolution processing on the target image to obtain a second image.

a second processing unit 5022, configured to perform grayscale processing on the second picture to obtain a third picture;

The third processing unit 5023 is configured to perform a histogram equalization process on the third picture to obtain a pre-processed picture.

The detecting module 503 is configured to perform edge detection on the preprocessed picture to count the number N of edge points, where N is a positive integer.

Optionally, the detecting module 503 further includes:

The detecting unit 5031 is configured to perform edge detection on the M pixel points in the preset area of the preprocessed picture to obtain M detection values, where the M detection values are in one-to-one correspondence with the M pixel points;

The statistic unit 5032 is configured to use a pixel point corresponding to the second threshold value of the M detection values as an edge point to count the number N of edge points, where the M is greater than or equal to N.

Optionally, the detecting mode 303 is specifically configured to: perform edge detection on M pixel points in a preset area of the preprocessed picture by using a detection operator.

The determining module 504 is configured to use the first picture to determine a target video file type when the N is greater than or equal to the first threshold.

Wherein, when the N is less than the first threshold, the apparatus 500 includes:

The second obtaining module 505 is configured to obtain a fourth picture, where the fourth picture is a frame picture different from the first picture in the target video file, and the picture quality evaluation operation is performed again based on the fourth picture.

It should be noted that each of the above modules (the first obtaining module 501, the processing module 502, the detecting module 503, the determining module 504, and the second acquiring module 505) is configured to execute the related steps of the method for determining the driving trajectory.

The "module" in this embodiment may be an application-specific integrated circuit (ASIC), a processor and memory that executes one or more software or firmware programs, integrated logic circuits, and/or others that may provide the above functions. Device. In addition, the first acquiring module 501, The processing module 502, the detecting module 503, the determining module 504, and the second obtaining module 505 can be implemented by a processor in the apparatus 800 described in FIG.

As shown in FIG. 8, the picture quality evaluation apparatus can be implemented by the structure in FIG. The apparatus 800 includes at least one processor 801, at least one memory 802, and at least one communication interface 803. In addition, the device may also include general components such as an antenna, which will not be described in detail herein.

The processor 801 can be a general purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of the above program.

The communication interface 803 is configured to communicate with other devices or communication networks, such as Ethernet, Radio Access Network (RAN), Wireless Local Area Networks (WLAN), and the like.

The memory 802 can be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type that can store information and instructions. The dynamic storage device can also be an Electrically Erasable Programmable Read-Only Memory (EEPROM), a Compact Disc Read-Only Memory (CD-ROM) or other optical disc storage, and a disc storage device. (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or can be used to carry or store desired program code in the form of instructions or data structures and can be Any other media accessed, but not limited to this. The memory can exist independently and be connected to the processor via a bus. The memory can also be integrated with the processor.

The memory 802 is configured to store application code that executes the above solution, and is controlled by the processor 801 for execution. The processor 801 is configured to execute application code stored in the memory 802.

The picture quality evaluation apparatus shown in FIG. 8 , the code stored in the memory 802 can perform the image quality evaluation method provided above, for example, the picture quality evaluation apparatus acquires the first picture; and preprocesses the first picture to obtain a preprocessed picture; Edge detection is performed on the preprocessed picture to count the number N of edge points, where N is a positive integer; when the N is greater than or equal to the first threshold, the first picture is used to determine a target video file. Types of.

The embodiment of the present invention further provides a computer storage medium, wherein the computer storage medium may store a program, and the program includes some or all of the steps of any one of the picture quality evaluation methods described in the foregoing method embodiments.

It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should understand that the present invention is not limited by the described action sequence. Because certain steps may be performed in other sequences or concurrently in accordance with the present invention. In addition, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

In the above embodiments, the descriptions of the various embodiments are different, and the details that are not detailed in a certain embodiment can be referred to the related descriptions of other embodiments.

In the several embodiments provided herein, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the unit is only a logical function division. In actual implementation, there may be another division manner, for example, multiple units or components may be combined or may be Integrate into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be electrical or otherwise.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present invention may contribute to the prior art or all or part of the technical solution may be embodied in the form of a software product stored in a memory. A number of instructions are included to cause a computer device (which may be a personal computer, server or network device, etc.) to perform all or part of the steps of the methods of the various embodiments of the present invention. The foregoing memory includes: a U disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk, and the like, which can store program codes.

A person skilled in the art can understand that all or part of the steps of the foregoing embodiments can be completed by a program to instruct related hardware, and the program can be stored in a computer readable memory, and the memory can include: a flash drive , read-only memory (English: Read-Only Memory, referred to as: ROM), random accessor (English: Random Access Memory, referred to as: RAM), disk or CD.

The embodiments of the present invention have been described in detail above, and the principles and implementations of the present invention are described in detail herein. The description of the above embodiments is only for helping to understand the method of the present invention and its core ideas; The present invention is not limited by the scope of the present invention, and the present invention is not limited by the scope of the present invention.

Claims

A picture quality evaluation method, characterized in that it comprises:

Get the first picture;

Performing pre-processing on the first picture to obtain a pre-processed picture;

Performing edge detection on the preprocessed picture to count the number N of edge points, where N is a positive integer;

The first picture is used to determine a target video file type when the N is greater than or equal to a first threshold.
The method according to claim 1, wherein the first picture is a frame picture in the target video file.
The method of claim 2 wherein said first picture is a key frame in said target video file.
The method according to any one of claims 1-3, wherein the pre-processing the first picture to obtain a pre-processed picture comprises:

Performing resolution processing on the first picture to obtain a second picture;

Performing grayscale processing on the second picture to obtain a third picture;

Performing a histogram equalization process on the third picture to obtain a preprocessed picture.
The method according to claim 4, wherein the performing edge detection on the preprocessed picture to count the number N of edge points comprises:

Edge detection is performed on M pixel points in the preset area of the preprocessed picture to obtain M detection values, and the M detection values are in one-to-one correspondence with the M pixel points;

A pixel point corresponding to the second threshold value of the M detection values is used as an edge point to count the number N of edge points, and the M is greater than or equal to N.
The method according to claim 4, wherein the performing edge detection on the M pixels in the preset area of the preprocessed picture comprises:

Edge detection is performed on M pixel points in a preset area of the preprocessed picture by a detection operator.
The method of claim 6 wherein when said N is less than the first threshold, The methods include:

Obtaining a fourth picture, where the fourth picture is a frame picture different from the first picture in the target video file;

Performing a picture quality evaluation operation based on the fourth picture.
A picture quality evaluation device, comprising:

a first acquiring module, configured to acquire a first picture;

a processing module, configured to perform pre-processing on the first picture to obtain a pre-processed picture;

a detecting module, configured to perform edge detection on the preprocessed picture to count the number N of edge points, where N is a positive integer;

And a determining module, configured to use the first picture to determine a target video file type when the N is greater than or equal to the first threshold.
The apparatus according to claim 8, wherein the first picture is a frame picture in the target video file.
The apparatus of claim 9, wherein the first picture is a key frame in the target video file.
The apparatus according to any one of claims 8 to 10, wherein the processing module comprises:

a first processing unit, configured to perform resolution processing on the first picture to obtain a second picture;

a second processing unit, configured to perform grayscale processing on the second image to obtain a third image;

And a third processing unit, configured to perform a histogram equalization process on the third picture to obtain a pre-processed picture.
The device according to claim 11, wherein the detecting module comprises:

The detecting unit is configured to perform edge detection on the M pixels in the preset area of the preprocessed picture to obtain M detection values, where the M detection values are in one-to-one correspondence with the M pixel points;

And a statistical unit, configured to use, as an edge point, a pixel point corresponding to the second threshold value of the M detection values, to count the number N of edge points, where the M is greater than or equal to N.
The device according to claim 11, wherein said detecting mold body is for:

Edge detection is performed on M pixel points in a preset area of the preprocessed picture by a detection operator.
The device according to claim 13, wherein when the N is smaller than the first threshold, the device comprises:

a second acquiring module, configured to acquire a fourth picture, where the fourth picture is a frame picture different from the first picture in the target video file, and the picture quality evaluation operation is performed again based on the fourth picture.
A picture quality evaluation device, comprising:

a memory storing executable program code;

a processor coupled to the memory;

The processor invokes the executable program code stored in the memory to perform the method of claims 1-7.