CN114095722A

CN114095722A - Definition determining method, device and equipment

Info

Publication number: CN114095722A
Application number: CN202111172751.8A
Authority: CN
Inventors: 李睿鑫; 张炯
Original assignee: Dingtalk China Information Technology Co Ltd
Current assignee: Dingtalk China Information Technology Co Ltd
Priority date: 2021-10-08
Filing date: 2021-10-08
Publication date: 2022-02-25
Also published as: WO2023056896A1

Abstract

The embodiment of the application provides a definition determining method, a definition determining device and definition determining equipment. The method comprises the following steps: the method comprises the steps of obtaining a reference video frame sequence of a sending end and a receiving video frame sequence correspondingly played by a receiving end, aiming at a receiving video frame in the receiving video frame sequence, determining a reference video frame corresponding to the receiving video frame from the reference video frame sequence according to a frame mark of the receiving video frame, and calculating the definition of the receiving video frame by adopting a referenced image definition evaluation algorithm according to the receiving video frame in the receiving video frame sequence and the reference video frame corresponding to the receiving video frame. The labor cost can be saved.

Description

Definition determining method, device and equipment

Technical Field

The present application relates to the field of internet technologies, and in particular, to a method, an apparatus, and a device for determining sharpness.

Background

With the continuous development of internet technology, video systems such as video conference systems and video live broadcast systems are also more and more widely applied.

In a video quality evaluation system of a video system, the definition of a video received by a receiving end is an important evaluation dimension. Often, manual involvement is required to determine the sharpness of the video received at the receiving end. However, the way of manually participating in definition determination has the problem of high labor cost.

Disclosure of Invention

The embodiment of the application provides a definition determining method, a definition determining device and definition determining equipment, which are used for solving the problem that in the prior art, labor cost is high in a manner of manually participating in definition determination.

In a first aspect, an embodiment of the present application provides a method for determining sharpness, including:

acquiring a reference video frame sequence of a sending end and a receiving video frame sequence correspondingly played by a receiving end, wherein video frames in the reference video frame sequence and the receiving video frame sequence have frame identifications, and the same frame identification corresponds to the same video frame;

determining a reference video frame corresponding to a received video frame from the reference video frame sequence according to a frame identifier of the received video frame in the received video frame sequence;

and calculating the definition of the received video frame by adopting a referenced image definition evaluation algorithm according to the received video frame in the received video frame sequence and a corresponding reference video frame.

In a second aspect, an embodiment of the present application provides a device for determining sharpness, including:

the device comprises an acquisition module, a display module and a display module, wherein the acquisition module is used for acquiring a reference video frame sequence of a sending end and a receiving video frame sequence correspondingly played by a receiving end, video frames in the reference video frame sequence and the receiving video frame sequence have frame identifications, and the same frame identification corresponds to the same video frame;

a determining module, configured to determine, according to a frame identifier of a received video frame in the received video frame sequence, a reference video frame corresponding to the received video frame from the reference video frame sequence;

and the evaluation module is used for calculating the definition of the received video frame by adopting a referenced image definition evaluation algorithm according to the received video frame in the received video frame sequence and a corresponding reference video frame.

In a third aspect, an embodiment of the present application provides an electronic device, including: a memory, a processor; wherein the memory is to store one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement the method of any of the first aspects.

Embodiments of the present application also provide a computer-readable storage medium storing a computer program, the computer program comprising at least one piece of code executable by a computer to control the computer to perform the method according to any one of the first aspect.

Embodiments of the present application also provide a computer program, which when executed by a computer, is configured to implement the method according to any one of the first aspect.

The definition determining method, the device and the equipment provided by the embodiment of the application obtain a reference video frame sequence of a sending end and a receiving video frame sequence correspondingly played by a receiving end, determine a reference video frame corresponding to the receiving video frame from the reference video frame sequence according to a frame identifier of the receiving video frame aiming at the receiving video frame in the receiving video frame sequence, and calculate the definition of the receiving video frame according to the receiving video frame in the receiving video frame sequence and the corresponding reference video frame thereof by adopting a referenced image definition evaluation algorithm, thereby realizing the automatic definition of the video frame of the receiving end without manual participation, and saving the labor cost.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative efforts.

Fig. 1 is a schematic view of an application scenario according to an embodiment of the present application;

fig. 2 is a schematic flowchart of a definition determining method according to an embodiment of the present disclosure;

fig. 3 is a flowchart illustrating a method for determining sharpness according to an embodiment of the present disclosure;

fig. 4A is a schematic diagram of a video frame according to an embodiment of the present application;

FIG. 4B is a diagram of a video frame obtained after frame marking the video frame shown in FIG. 4A;

fig. 5 is a flowchart illustrating a method for determining sharpness according to another embodiment of the present disclosure;

FIG. 6A is a schematic diagram of a process for determining a target reference video frame sequence and a target received video frame sequence according to an embodiment of the present application;

FIG. 6B is a schematic diagram of a sequence of target reference video frames according to an embodiment of the present application;

FIG. 7 is a graph of sharpness provided by an embodiment of the present application;

FIG. 8A is a diagram of a video frame according to an embodiment of the present application;

FIG. 8B is a diagram of a video frame according to another embodiment of the present application;

FIG. 9 is a schematic diagram of a sequence of test video frames being split into a plurality of subsequences according to an embodiment of the present application;

fig. 10 is a schematic structural diagram of a sharpness determining apparatus according to an embodiment of the present application;

fig. 11 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The terminology used in the embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the examples of this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise, and "a" and "an" typically include at least two, but do not exclude the presence of at least one.

It should be understood that the term "and/or" as used herein is merely one type of association that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.

The words "if", as used herein, may be interpreted as "at … …" or "at … …" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrases "if determined" or "if detected (a stated condition or event)" may be interpreted as "when determined" or "in response to a determination" or "when detected (a stated condition or event)" or "in response to a detection (a stated condition or event)", depending on the context.

It is also noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a good or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such good or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a commodity or system that includes the element.

In addition, the sequence of steps in each method embodiment described below is only an example and is not strictly limited.

For the convenience of those skilled in the art to understand the technical solutions provided in the embodiments of the present application, a technical environment for implementing the technical solutions is described below.

Compared with a commonly used definition determining method in the related art, the definition of a video received by a receiving end needs to be determined manually, and the labor cost is high. The following modes 1 and 2 are specific to the determination of sharpness by manual participation in the related art.

Mode 1, a collection of observers are selected to view a plurality of "video pairs" of reference video and distorted video in a particular controlled environment, and each time view the reference video first and then view the distorted video. The observer judges the overall impression of the video, expresses the judgment by defined subjective measure and scores the definition effect of the video. The score was 5 points and the scoring criteria are shown in table 1 below.

TABLE 1

And 2, evaluating the definition of the horn line part in the analysis force test chart, cutting the horn line part out and embedding the horn line part into the video to obtain a video containing the horn line part, and evaluating the definition by observing the horn line in the video of the receiving end. Since the use of the horn wire requires manual data reading, the involvement of a tester is required.

Therefore, there is a need in the art for a definition determination method that can save labor cost.

Based on the actual technical requirements similar to those described above, the definition determination method provided by the application can save labor cost by using a technical means.

The method for providing sharpness provided by the embodiments of the present application is specifically described below by an exemplary application scenario.

As shown in fig. 1, an application scenario of the embodiment of the present application may include: a sending end 11 and a receiving end 12 in the video system, and the sending end 11 and the receiving end 12 can be connected through a communication network 13. The sender 11 may be configured to send a sequence of video frames, and the receiver 12 may correspond to receive the sequence of video frames sent by the sender 11. The transmitting end 11 and the receiving end 12 may be terminals such as a mobile phone, a tablet computer, a desktop computer, and a notebook computer. The video system may be, for example, a video conference system, a video live system, or the like that can be used to transmit video.

In one embodiment, the communication network 13 may be a weak network environment with poor network quality, so as to perform sharpness determination on the video frame at the receiving end in the weak network environment.

A sequence of reference video frames (hereinafter referred to as a sequence of reference video frames) to which sharpness determination is required to be referenced is available from the sender 11, and a sequence of received video frames (hereinafter referred to as a sequence of received video frames) to which sharpness determination is directed and which correspond to the sequence of reference video frames is available from the receiver 12. The video frames in the reference video frame sequence and the received video frame sequence have frame identifications, and the same frame identification corresponds to the same video frame. The frame identification is used to uniquely identify the video frame. It should be noted that, due to the influence of the communication network, the video frame data of the same video frame in the reference video frame sequence may not be identical to the video frame data of the video frame sequence when the video frame sequence is received.

As shown in fig. 1, the application scenario may further include an electronic device 14 for performing sharpness determination, and the electronic device 14 may determine sharpness of a video frame by using the method provided in the embodiment of the present application. Specifically, the electronic device 14 may obtain a reference video frame sequence of the sending end 11 and a receiving video frame sequence correspondingly played by the receiving end 12, determine, for a receiving video frame in the receiving video frame sequence, a reference video frame corresponding to the receiving video frame from the reference video frame sequence according to a frame identifier of the receiving video frame, and calculate, according to the receiving video frame in the receiving video frame sequence and the reference video frame corresponding to the receiving video frame, a definition evaluation algorithm with a reference to obtain a definition of the receiving video frame.

It should be noted that, in fig. 1, the electronic device 14 directly obtains the reference video frame sequence and the received video frame sequence from the sender 11 and the receiver 12 as an example, it is understood that in other embodiments, the electronic device 14 may obtain the reference video frame sequence and the received video frame sequence in other manners.

It should be noted that, in fig. 1, an electronic device 14 other than the sending end 11 and the receiving end 12 executes the method provided in the embodiment of the present application as an example, and it is understood that in other embodiments, the sending end 11 or the receiving end 12 may also execute the method provided in the embodiment of the present application.

According to the definition determining method provided by the embodiment of the application, the definition of the received video frame is calculated by acquiring the reference video frame sequence of the sending end and the received video frame sequence correspondingly played by the receiving end, wherein the reference video frame sequence and the video frames in the received video frame sequence have frame identifications, the same frame identification corresponds to the same video frame, the reference video frame corresponding to the received video frame is determined from the reference video frame sequence according to the frame identification of the received video frame in the received video frame sequence, and the definition of the video frame at the receiving end is automatically determined by adopting a referenced image definition evaluating algorithm according to the received video frame in the received video frame sequence and the corresponding reference video frame thereof, so that the labor cost can be saved.

Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the features of the embodiments can be combined with each other without conflict.

Fig. 2 is a flowchart illustrating a method for determining sharpness according to an embodiment of the present disclosure, where an execution subject of the embodiment may be the electronic device 14 in fig. 1. As shown in fig. 2, the method of this embodiment may include:

step 21, acquiring a reference video frame sequence of a sending end and a receiving video frame sequence correspondingly played by a receiving end, wherein video frames in the reference video frame sequence and the receiving video frame sequence have frame identifications, and the same frame identification corresponds to the same video frame;

step 22, determining a reference video frame corresponding to a received video frame from the reference video frame sequence according to a frame identifier of the received video frame in the received video frame sequence;

and step 23, calculating the definition of the received video frame by using a referenced image definition evaluation algorithm according to the received video frame in the received video frame sequence and a reference video frame corresponding to the received video frame.

As shown in fig. 3, a test video frame sequence with frame identification marks made in advance may be injected into a sending end through a "video capture hook" module, and the test video frame sequence may be sent to a receiving end through a weak network environment after being encoded by a "video encoding" module of the sending end. At the receiving end, the received video frame sequence may be acquired through a "video playing hook" after the received test video frame sequence is decoded through a "video decoding" module.

The test video frame sequence is a video frame sequence which is marked with frame identification in advance and used for testing the definition of a receiving end in a video system. The specific mode of marking the frame identification can be flexibly realized. In one embodiment, the frame identification of the sequence of test video frames is in the form of image content contained in a target area of the video frames. Accordingly, the frame identifications of the video frames in the sequence of reference video frames and the sequence of received video frames may be in the form of image content contained in the target area of the video frames.

In one embodiment, the test video frame sequence may be obtained by replacing image content in a target region of each video frame in the original video frame sequence with frame identification content. Taking a video frame in the original video frame sequence as shown in fig. 4A as an example, after marking the video frame shown in fig. 4A with a frame identifier, the video frame shown in fig. 4B can be obtained. The image content "0123" in the target region in fig. 4B is the frame identifier of the video frame.

It should be noted that the position and the shape of the target area in fig. 4B are only examples, and in other embodiments, the target area may have other shapes and may be located at other positions. It should be noted that, in fig. 4B, the frame identification content is specifically a number as an example, in other embodiments, the frame identification may also be in other forms, for example, different shapes may also be used as the frame identification content.

For example, the weak network environment in fig. 3 may be obtained through simulation to simulate various network impairments in network transmission, such as packet loss, delay, and the like. In one embodiment, the weak network environment may be simulated based on a Traffic Control (TC) module provided by the Linux system, where the TC module is a software module and may set a delay, a packet loss rate, and the like.

For example, a weak network environment may be simulated using a wireless cloud routing-C1B router that implements a TC module. The sending end can be connected with a WAN port of the CIB router, the receiving end can be connected with a LAN port of the C1B router, the C1B router is connected with the Internet, and the weak network environment can be simulated by controlling a TC module of the C1B router. In addition, since the TC module controls the outlet, and the WAN port and the LAN port of the C1B router may be outlets to each other, bidirectional flow control between the transmitting end and the receiving end may be achieved by controlling the TC module by making the WAN port and the LAN port of the C1B router be outlets to each other. Of course, in other embodiments, the weak network environment may be obtained in other manners, which is not limited in this application.

In fig. 3, a "video capture hook" may use a hook (hook) technique in a software manner to inject a sequence of test video frames to a transmitting end of a video system. In the video system, a video frame sequence acquired by a camera is acquired by calling an acquisition function provided by an operating system, and a video acquisition hook module can realize that a hook technology in a software mode is adopted to inject a test video frame sequence into a sending end of the video system by replacing the calling acquisition function with a specific function for acquiring the test video frame sequence.

Alternatively, a hardware hook technique may be used to inject a sequence of test video frames to the sender of a video system. The method comprises the steps that an original video frame sequence can be acquired by a terminal and marked to obtain a test video frame sequence, a video acquisition card is connected with the terminal and acquires the test video frame sequence from the terminal, and the video acquisition card is connected with a sending end and serves as video acquisition equipment of the sending end, so that the test video frame can be injected into the sending end through a hook technology in a hardware mode.

In fig. 3, "video playing hook" may obtain the received video frame sequence at the receiving end by using a hook technology in a software manner. In the video system, the receiving end may render the video data by calling a rendering function provided by the operating system, and the "video playing hook" module may obtain the received video frame sequence of the receiving end by using a hook technology in a software manner in a manner of intercepting data from the rendering function.

Alternatively, a hardware hook technique may be used to obtain the received video frame sequence at the receiving end. The receiving end can be connected with a video acquisition card, and the video acquisition card acquires a received video frame sequence from the receiving end.

In one embodiment, as shown in fig. 3, sharpness may be determined from a sequence of test video frames and a sequence of received video frames, i.e. the sequence of reference video frames may be a sequence of test video frames input to the sender. In this case, if the pixels of the video frame in the test video frame sequence are not aligned with the pixels of the video frame in the received video frame sequence, the video frame may be cropped and scaled, so that the video frame and the video frame can be aligned with each other, and then the sharpness determination may be performed by using an image sharpness algorithm with a reference.

In another embodiment, as shown in fig. 5, the definition may be determined according to a video frame sequence obtained by locally rendering a test video frame sequence input to the transmitting end by the transmitting end and a received video frame sequence, that is, the reference video frame sequence may be a video frame sequence obtained by locally rendering an input test video frame sequence by the transmitting end. The video frame sequence obtained by locally rendering the test video frame sequence can be obtained by a hook technique.

The reference video frame sequence is a video frame sequence obtained by locally rendering the test video frame sequence by the sending end, and the layouts of user interfaces aimed at by the local rendering of the sending end and the receiving end are the same, so that the video frames in the reference video frame sequence and the video frames in the received video frame sequence can be aligned in a pixel level, the cutting and scaling processing for realizing the pixel alignment can be omitted, and the simplification of the realization is facilitated.

It should be noted that the contents of the other parts in fig. 5 are similar to those in fig. 3, and are not described again here.

In the embodiment of the application, after the reference video frame sequence and the received video frame sequence are obtained, the reference video frame corresponding to the received video frame may be determined from the reference video frame sequence according to the frame identifier of the received video frame in the received video frame sequence. It should be understood that in the sequence of reference video frames, a reference video frame having the same frame identification as a received video frame is a reference video frame corresponding to the received video frame.

Optionally, in the case that the frame identifier is included in the target area of the video frame in the form of image content, step 22 may further include: and respectively identifying the image content of the target area in each video frame of the reference video frame sequence and the receiving video frame sequence to obtain the frame identification of each video frame in the reference video frame sequence and the receiving video frame sequence. The adopted Recognition technology may be, for example, Optical Character Recognition (OCR), an object detection technology, and the like, and certainly, in other embodiments, other types of technologies may also be adopted to recognize the image content of the object region, which is not limited in this application.

In the embodiment of the application, after the reference video frame corresponding to the received video frame is determined in the sequence of reference video frames, the definition of the received video frame can be calculated by using a referenced image definition evaluation algorithm according to the received video frame and the reference video frame corresponding to the received video frame.

Optionally, in a case that the frame identifier is included in the target area of the video frame in the form of image content, step 23 may specifically include: cropping the target areas of the reference video frame and the received video frame; and calculating the definition of the received video frame by adopting a reference image definition evaluation algorithm according to the cut received video frame and the corresponding cut reference video frame. By cutting off the target areas of the reference video frame and the received video frame for bearing the frame identification content and calculating the definition according to the cutting result, the influence of the frame identification content on the definition calculation can be avoided, and the definition determination accuracy can be improved.

In practical applications, a situation may occur in which a certain video frame exists in the reference video frame sequence but does not exist in the received video frame sequence due to packet loss or the like.

In practice, it may also happen that a certain video frame is present in the sequence of received video frames and not in the sequence of reference video frames. For example, when the reference video frame sequence is a video frame sequence obtained by locally rendering a test video frame sequence at a sending end, a frame loss may occur when the video frame sequence obtained by locally rendering is obtained by a hook technique, and thus a certain video frame may exist in the received video frame sequence but does not exist in the reference video frame sequence.

In this case, the step 23 may specifically include: arranging specific frame identification sequences of target reference video frames corresponding to the received video frames in the reference video frame sequence to obtain a target reference video frame sequence; arranging target receiving video frames with corresponding reference video frames in the receiving video frame sequence according to the specific frame identification sequence to obtain a target receiving video frame sequence; and calculating the definition of the target receiving video frame by adopting a referenced image definition evaluation algorithm according to the target receiving video frame at each position in the target receiving video frame sequence and the target reference video frame at the position in the target reference video frame sequence.

For example, as shown in fig. 6A, assuming that the video frames included in the reference video frame sequence are video frames with

frame identifications

1, 2, 4 and 5, respectively, and the video frames included in the received video frame sequence are video frames with

frame identifications

1, 2, 3 and 5, respectively, the obtained target reference video frame sequence may be a video frame sequence composed of video frames with

frame identifications

1, 2 and 5 in the reference video frame sequence, and the obtained target received video frame sequence may be a video frame sequence composed of video frames with

frame identifications

1, 2 and 5 in the received video frame sequence. It should be noted that, the target reference video frame and the target received video frame that are obtained by arranging the frame identifiers in the order from small to large in fig. 6A are only examples.

It will be appreciated that in the case where the video frames in the sequence of received video frames are a subset of the sequence of reference video frames, the sequence of target reference video frames may be derived from the sequence of received video frames and the sequence of reference video frames only, and the sequence of target received video frames may be the same as the sequence of received video frames. For example, as shown in fig. 6B, assuming that the video frames included in the reference video frame sequence are respectively video frames with

frame identifications

1, 2, 3 and 4, and the video frames included in the received video frame sequence are respectively video frames with

frame identifications

1, 2 and 3, the resulting target reference video frame sequence may be a video frame sequence composed of video frames with

frame identifications

1, 2 and 3 in the reference video frame sequence.

Taking the target reference video frame sequence and the target receiving video frame sequence both including video frames with frame identifiers 1, 2, and 5 as examples, calculating the sharpness of the target receiving video frame according to the target receiving video frame at each position in the target receiving video frame sequence and the target reference video frame at the position in the target reference video frame sequence by using an image sharpness evaluation algorithm with reference, for example, may include: firstly, according to a video frame with a frame identifier of 1 in a target reference video frame sequence and a video frame with a frame identifier of 1 in a target receiving video frame sequence, calculating by adopting a referenced image definition evaluation algorithm to obtain the definition of the video frame with the frame identifier of 1 in the target receiving video frame sequence; then, according to the video frame with the frame mark of 2 in the target reference video frame sequence and the video frame with the frame mark of 2 in the target receiving video frame sequence, calculating by adopting a reference image definition evaluation algorithm to obtain the definition of the video frame with the frame mark of 2 in the target receiving video frame sequence; and calculating by adopting a referenced image definition evaluation algorithm according to the video frame with the frame identifier of 5 in the target reference video frame sequence and the video frame with the frame identifier of 5 in the target receiving video frame sequence to obtain the definition of the video frame with the frame identifier of 5 in the target receiving video frame sequence.

The reference image sharpness evaluation algorithm may be, for example, Peak Signal to Noise Ratio (PSNR) algorithm, Video multi-method Assessment Fusion (VMAF) algorithm, or the like. Of course, in other embodiments, other image sharpness evaluation algorithms with reference may also be adopted, and the present application is not limited thereto.

Taking the example of calculating the definition of a video frame Y by using a PSNR algorithm according to a video frame X identified by a certain frame in a reference video frame sequence and a video frame Y identified by the frame in a received video frame sequence, the definition P of the video frame Y can be calculated by using the following formula (1).

Wherein L represents the maximum pixel value possible in a video frame, for example, the maximum pixel value of a video frame using 8 bits to represent pixel values may be 255; the MSE satisfies the following equation (2).

Where M N represents an image where both video frame X and video frame Y are M N, X_ijDenotes the pixel value, y, of a pixel with pixel coordinates (i, j) in the video frame X_ijA pixel value of a pixel having a pixel coordinate (i, j) in the video frame Y is represented.

Taking as an example that the definition of each video frame in the target received video frame sequence is calculated by using the PSNR algorithm and the VMAF algorithm according to the target reference video frame sequence and the target received video frame sequence respectively in the scene of the motion of the person, the obtained definition of each video frame may be as shown in fig. 7, for example. The abscissa in fig. 7 may represent the 0 th frame, the 1 st frame, the 2 nd frame, etc. in the target received video frame sequence, and the ordinate may represent the sharpness, the upper curve in fig. 7 may represent the sharpness curve calculated by the VMAF algorithm, and the lower curve in fig. 7 may represent the sharpness curve calculated by the PSNR algorithm.

The higher the definition in fig. 7 is, the clearer the video frame is, and the change of the definition curve can reflect the actual definition of the corresponding picture. For example, for a video frame with higher definition in fig. 7, a picture of the video frame (e.g., as shown in fig. 8A) is viewed to find that there is a small motion in the picture of the video frame. For another example, in a certain video frame with high definition in fig. 7, a picture of the video frame (for example, as shown in fig. 8B) is checked to find that the picture of the video frame has a large motion, and when the motion degree is large, the main phenomenon of the reduction of definition occurs is that a mosaic is generated on the picture, which is an expression of insufficient bitrate.

In the embodiment of the application, after the definition of the received video frame is determined, the definition of a plurality of received video frames in the received video frame sequence can be counted to obtain a definition counting result. Through carrying out statistical calculation on the definition, a definition statistical result is obtained, so that the definition condition of a receiving end can be obtained from a statistical angle. Illustratively, the statistical manner may specifically be an average.

In an embodiment, the segmenting the sequence of test video frames into a plurality of subsequences, and performing statistical calculation on the definitions of a plurality of received video frames may specifically include: and counting the definition of a plurality of received video frames corresponding to the same subsequence by taking each subsequence as a unit to obtain definition counting results corresponding to the plurality of subsequences respectively.

For example, as shown in fig. 9, the sequence of test video frames may be temporally split into sub-sequence 1, sub-sequence 2, and sub-sequence 3. Assuming that the frame identifiers of the video frames included in the subsequence 1 are 1 to 100, the frame identifiers of the video frames included in the subsequence 2 are 101 to 200, and the frame identifiers of the video frames included in the subsequence 3 are 201 to 300, the definitions of the received video frames with the frame identifiers of 1 to 100 may be averaged to obtain a definition statistical result corresponding to the subsequence 1, the definitions of the received video frames with the frame identifiers of 101 to 200 may be averaged to obtain a definition statistical result corresponding to the subsequence 2, and the definitions of the received video frames with the frame identifiers of 201 to 300 may be averaged to obtain a definition statistical result corresponding to the subsequence 3.

According to the definition determining method provided by the embodiment of the application, the reference video frame corresponding to the received video frame is determined from the reference video frame sequence according to the frame identification of the received video frame by acquiring the reference video frame sequence of the sending end and the received video frame sequence correspondingly played by the receiving end aiming at the received video frame in the received video frame sequence, and the definition of the received video frame is calculated according to the received video frame in the received video frame sequence and the reference video frame corresponding to the received video frame by adopting the image definition evaluating algorithm with reference, so that the definition of the video frame of the receiving end is automatically determined without manual participation, and the labor cost can be saved.

Fig. 10 is a schematic structural diagram of a sharpness determining apparatus according to an embodiment of the present application; referring to fig. 10, the present embodiment provides a definition determining apparatus, which may perform the definition determining method described above, and specifically, the definition determining apparatus may include:

an obtaining module 101, configured to obtain a reference video frame sequence at a sending end and a receiving video frame sequence correspondingly played at a receiving end, where video frames in the reference video frame sequence and the receiving video frame sequence have frame identifiers, and the same frame identifier corresponds to the same video frame;

a determining module 102, configured to determine, according to a frame identifier of a received video frame in the received video frame sequence, a reference video frame corresponding to the received video frame from the reference video frame sequence;

the evaluation module 103 is configured to calculate, according to a received video frame in the received video frame sequence and a reference video frame corresponding to the received video frame, a definition of the received video frame by using a reference image definition evaluation algorithm.

Optionally, the reference video frame sequence is a video frame sequence obtained by locally rendering a test video frame sequence by the sending end, the test video frame sequence is sent to the receiving end by the sending end, and layouts of user interfaces for local rendering by the sending end and the receiving end are the same.

Optionally, the frame identifier is contained in the form of image content in a target area of the video frame; the determining module 102 is further configured to: and respectively identifying the image content of the target area in each video frame of the reference video frame sequence and the received video frame sequence to obtain the frame identification of each video frame in the reference video frame sequence and the received video frame sequence.

Optionally, the evaluation module 103 is specifically configured to: cropping the target areas of the reference video frame and the received video frame; and calculating the definition of the received video frame by adopting a reference image definition evaluation algorithm according to the cut reference video frame and the cut video frame.

Optionally, the evaluation module 103 is specifically configured to: arranging specific frame identification sequences of target reference video frames corresponding to the received video frames in the reference video frame sequence to obtain a target reference video frame sequence; arranging target receiving video frames with corresponding reference video frames in the receiving video frame sequence according to the specific frame identification sequence to obtain a target receiving video frame sequence; and calculating the definition of the target receiving video frame by adopting a referenced image definition evaluation algorithm according to the target receiving video frame at each position in the target receiving video frame sequence and the target reference video frame at the position in the target reference video frame sequence.

Optionally, the apparatus further includes a statistics module, configured to perform statistics calculation on the sharpness of multiple received video frames in the received video frame sequence to obtain a sharpness statistics result.

Optionally, the sequence of test video frames sent by the sending end to the receiving end is segmented into a plurality of subsequences, and the statistics module 103 is specifically configured to: and counting the definition of a plurality of received video frames corresponding to the same subsequence by taking each subsequence as a unit to obtain definition counting results corresponding to the plurality of subsequences respectively.

The apparatus shown in fig. 10 can perform the method provided by the embodiment shown in fig. 2, and reference may be made to the related description of the embodiment shown in fig. 2 for a part not described in detail in this embodiment. The implementation process and technical effect of the technical solution refer to the description in the embodiment shown in fig. 2, and are not described herein again.

In one possible implementation, the structure of the sharpness determining apparatus shown in fig. 10 may be implemented as an electronic device. As shown in fig. 11, the electronic device may include: a processor 111 and a memory 112. Wherein the memory 112 is used for storing a program that supports the electronic device to execute the definition determining method provided in the embodiment shown in fig. 2, and the processor 111 is configured to execute the program stored in the memory 112.

The program comprises one or more computer instructions, wherein the one or more computer instructions, when executed by the processor 111, are capable of performing the steps of:

Optionally, the processor 111 is further configured to perform all or part of the steps in the foregoing embodiment shown in fig. 2.

The electronic device may further include a communication interface 113 configured to communicate with other devices or a communication network.

In addition, the present application provides a computer storage medium for storing computer software instructions for an electronic device, which includes a program for executing the method for determining sharpness in the method embodiment shown in fig. 2.

The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.

Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by adding a necessary general hardware platform, and of course, can also be implemented by a combination of hardware and software. With this understanding in mind, the above-described technical solutions and/or portions thereof that contribute to the prior art may be embodied in the form of a computer program product, which may be embodied on one or more computer-usable storage media having computer-usable program code embodied therein (including but not limited to disk storage, CD-ROM, optical storage, etc.).

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method of sharpness determination, comprising:

2. The method according to claim 1, wherein the reference video frame sequence is a video frame sequence obtained by the sending end locally rendering a test video frame sequence, the test video frame sequence is sent from the sending end to the receiving end, and the layouts of the user interfaces for which the sending end and the receiving end locally render are the same.

3. The method of claim 1, wherein the frame identification is included in the form of image content in a target area of a video frame; the method further comprises the following steps: and respectively identifying the image content of the target area in each video frame of the reference video frame sequence and the received video frame sequence to obtain the frame identification of each video frame in the reference video frame sequence and the received video frame sequence.

4. The method of claim 3, wherein calculating the sharpness of the received video frame according to the received video frame in the sequence of received video frames and a corresponding reference video frame by using an image sharpness evaluation algorithm with reference comprises:

cropping the target areas of the reference video frame and the received video frame;

and calculating the definition of the received video frame by adopting a reference image definition evaluation algorithm according to the cut received video frame and the corresponding cut reference video frame.

5. The method of claim 1, wherein calculating the sharpness of the received video frame according to the received video frame in the sequence of received video frames and a corresponding reference video frame by using an image sharpness evaluation algorithm with reference comprises:

arranging the frame identification specific sequence of the target reference video frame corresponding to the received video frame in the reference video frame sequence to obtain a target reference video frame sequence;

arranging target receiving video frames with corresponding reference video frames in the receiving video frame sequence according to the specific sequence of the frame identifiers to obtain a target receiving video frame sequence;

and calculating the definition of the target receiving video frame by adopting a referenced image definition evaluation algorithm according to the target receiving video frames at all positions in the target receiving video frame sequence and the target reference video frames at the positions in the target reference video frame sequence.

6. The method according to any one of claims 1-5, further comprising:

and carrying out statistical calculation on the definition of a plurality of received video frames in the received video frame sequence to obtain a definition statistical result.

7. The method according to claim 6, wherein the step of segmenting the sequence of test video frames sent by the sending end to the receiving end into a plurality of subsequences, and the step of performing statistical calculation on the sharpness of a plurality of received video frames in the sequence of received video frames to obtain a sharpness statistical result comprises:

and counting the definition of a plurality of received video frames corresponding to the same subsequence by taking each subsequence as a unit to obtain definition counting results corresponding to the plurality of subsequences respectively.

8. A sharpness determination apparatus, comprising:

9. The apparatus according to claim 8, wherein the reference video frame sequence is a video frame sequence obtained by the sending end locally rendering a test video frame sequence, the test video frame sequence is sent from the sending end to the receiving end, and a layout of a user interface for local rendering by the sending end and the receiving end is the same.

10. The apparatus of claim 8, wherein the frame identifier is included in the form of image content in a target area of a video frame; the determination module is further to: and respectively identifying the image content of the target area in each video frame of the reference video frame sequence and the received video frame sequence to obtain the frame identification of each video frame in the reference video frame sequence and the received video frame sequence.

11. The apparatus of claim 10, wherein the evaluation module is specifically configured to:

and calculating the definition of the received video frame by adopting a reference image definition evaluation algorithm according to the cut reference video frame and the cut video frame.

12. The apparatus of claim 8, wherein the evaluation module is specifically configured to:

arranging specific frame identification sequences of target reference video frames corresponding to the received video frames in the reference video frame sequence to obtain a target reference video frame sequence;

arranging target receiving video frames with corresponding reference video frames in the receiving video frame sequence according to the specific frame identification sequence to obtain a target receiving video frame sequence;

13. The apparatus according to any of claims 8-12, further comprising a statistics module configured to perform a statistical calculation on the sharpness of a plurality of received video frames in the sequence of received video frames to obtain a sharpness statistics result.

14. The apparatus according to claim 13, wherein the sequence of test video frames sent by the sending end to the receiving end is segmented into a plurality of subsequences, and the statistics module is specifically configured to: and counting the definition of a plurality of received video frames corresponding to the same subsequence by taking each subsequence as a unit to obtain definition counting results corresponding to the plurality of subsequences respectively.

15. An electronic device, comprising: a memory, a processor; wherein the memory is to store one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement the method of any of claims 1 to 7.