WO2023231710A1

WO2023231710A1 - Picture processing method and related device

Info

Publication number: WO2023231710A1
Application number: PCT/CN2023/092770
Authority: WO
Inventors: 赖昌材; 郭小东; 张海波; 钱璟; 裘杰; 周彦均
Original assignee: 华为技术有限公司
Priority date: 2022-05-30
Filing date: 2023-05-08
Publication date: 2023-12-07
Also published as: CN117221740A

Abstract

Embodiments of the present application disclose a picture processing method and a computer device, which can be used in the field of computer file management, and specifically in a decoding scenario and an encoding scenario of picture files. The method comprises: obtaining a first picture file; performing arithmetic decoding or asymmetric digital system decoding on the first picture file to obtain a first direct current coefficient and a first alternating current coefficient; performing inverse quantization and inverse discrete cosine transform on the first direct current coefficient and the first alternating current coefficient to obtain a picture file in a YUV format; and converting the picture file in the YUV format into a picture file in an RGB format. According to the method, the decoding process of the picture file is simplified, so that the processing procedure of the picture file is more flexible, and the system complexity and resource overhead are reduced.

Description

Image processing method and related equipment

Technical field

The present application relates to the field of computers, and in particular, to an image processing method and related equipment.

Background technique

With the popularity of terminals represented by smartphones, the proportion of media files (especially pictures) in existing smartphones and cloud storage is generally high, and as camera pixels continue to increase, the resolution of pictures is getting higher and higher. Each photo also takes up more and more storage space. At present, insufficient storage space has become one of the main factors for users to change mobile phones. Reducing the storage space required for pictures and improving storage space usage efficiency can greatly improve user experience and stickiness.

JPEG (joint photographic experts group, JPEG) is currently the most widely used picture standard (picture format). For the existing standard JPEG, there are already standard decoders that implement various technologies from JPEG decoding to display. With the development of technology, in order to improve the efficiency of storage space utilization, image files in JPEG format can be encoded into image files that require smaller storage space to achieve a lower space occupancy rate.

However, in the existing technology, the process of decoding the image files obtained after encoding the JPEG format image files and using them for display and other scenarios is relatively rigid and cumbersome, resulting in high system complexity and large resource overhead.

Contents of the invention

In view of the above technical problems, embodiments of the present application provide a picture processing method and computer equipment, which simplify the process of encoding or decoding picture files in the prior art, thereby making the picture file processing process more flexible and reducing the system cost. Complexity and resource overhead.

Based on this, the embodiments of this application provide the following technical solutions:

In the first aspect, embodiments of the present application first provide an image processing method (decoding process) for decoding an encoded image file into an RBG format image file for display. It can be applied to the client side to process pictures, and can also be used to the cloud side to process pictures. The method includes: obtaining a first picture file; performing arithmetic decoding or asymmetric digital system decoding on the first picture file to obtain the first The DC coefficient and the first AC coefficient; perform inverse quantization and inverse discrete cosine transformation on the first DC coefficient and the first AC coefficient to obtain a picture file in YUV format; convert the picture file in YUV format into an RGB format Image files.

The above picture processing method simplifies the process of secondary decoding (i.e., simplifies the process of decoding the first picture file into a picture file in a format such as JPEG), and simplifies the process of primary decoding (i.e., simplifies the process of decoding the first picture file into a picture file in a format such as JPEG). format image files into RGB format image files). That is to say, in the process of decoding the first picture file to obtain the picture file in RGB format, the step of generating picture files in JPEG and other formats is skipped, thereby avoiding unnecessary Huffman encoding operations and decoding operations. By simplifying the decoding process from the first image file to the RGB format image file, the image file processing process is made more flexible and system complexity and resource overhead are reduced.

In a possible implementation of the first aspect, the first picture file is obtained by encoding a second picture file, the format of the first picture file is different from the format of the second picture file, and the second picture file The image format of the file is any one of JPEG format, PNG format or GIF format.

In a possible implementation of the first aspect, the first picture file is stored in the memory. By way of example, the The first picture file can be stored in the local storage, or in the cloud or the storage of other electronic devices.

In a possible implementation of the first aspect, obtaining the first picture file specifically includes receiving the first picture file from the cloud or other electronic devices.

In a possible implementation of the first aspect, the image file in RGB format is used for display. It should be understood that the above method can also be applied in other scenarios other than display that require the use of image files in RGB format. For editing, sending and other scenarios that require the use of JPEG format image files, a complete second decoding process can be used to decode the first image file into a JPEG format image file.

For different application scenarios, using different decoding methods can reduce system complexity, improve system performance, and reduce resource utilization efficiency while ensuring function realization.

In a possible implementation of the first aspect, the process of performing inverse quantization and inverse discrete cosine transform on the first DC coefficient and the first AC coefficient to obtain the image file in YUV format does not include: Perform Huffman encoding on the DC coefficient and the first AC coefficient to obtain a picture file in JPEG format; perform Huffman decoding on the picture file in JPEG format to obtain the second DC coefficient and the second AC coefficient; The two DC coefficients and the second AC coefficient are subjected to inverse quantization and inverse discrete cosine transformation to obtain a picture file in YUV format.

In the second aspect, embodiments of the present application provide an image processing method (encoding process) for encoding an RGB format image file into an image format that requires less storage space and using it for storage. It can be applied to end-side devices or cloud-side devices. The method includes: obtaining an image file in RGB format; converting the image file in RGB format into an image file in YUV format; discretizing the image file in YUV format. Cosine transformation and quantization to obtain a third DC coefficient and a third AC coefficient; performing arithmetic coding or asymmetric digital system coding on the third DC coefficient and the third AC coefficient to obtain a third picture file, the third picture Files are used for storage in memory.

The above image processing method simplifies the primary encoding process (i.e., simplifies the process of encoding RGB format image files into JPEG and other format image files), and simplifies the secondary encoding process (i.e., simplifies the process of encoding JPEG format image files) The process of encoding image files in other formats into image files that require less storage space). That is to say, in the process of encoding image files in RGB format to obtain image files that require smaller storage space, the step of generating image files in JPEG and other formats is skipped, thereby avoiding unnecessary Huffman encoding operations and decoding operation. By simplifying the decoding process from RGB format image files to image files requiring smaller storage space, the processing of image files is made more flexible and system complexity and resource overhead are reduced.

In a possible implementation of the second aspect, the method further includes: performing arithmetic decoding or asymmetric decoding on the third picture file to obtain the third DC coefficient or the third AC coefficient; The AC coefficients are inversely quantized and inversely discrete cosine transformed to obtain image files in YUV format; the image files in YUV format are converted into image files in RGB format. This step can be used in subsequent scenarios where the third image file needs to be decoded to obtain an RGB format image file, for example, in display scenarios.

In a possible implementation of the second aspect, the method further includes: performing arithmetic decoding or asymmetric decoding on the third picture file to obtain the third DC coefficient or the third AC coefficient; The coefficients or third AC coefficients are Huffman encoded to obtain image files in JPEG format. This step can be used in subsequent scenarios where the third picture file needs to be decoded to obtain a picture file in a format such as JPEG, for example, in editing, sending, etc. scenarios.

According to the needs of different application scenarios, using different decoding methods for image files can reduce system complexity, improve system performance, and reduce resource utilization efficiency while ensuring function realization.

In a possible implementation of the second aspect, the third picture file can be stored in the memory. For example, the third picture file may be stored in a local storage, or may be stored in a cloud or the storage of other electronic devices. In the scenario of storing the third picture file in the cloud or the memory of other electronic devices, the method also includes: Send the third picture file to the cloud or other electronic device for storage.

In a possible implementation of the second aspect, arithmetic coding or asymmetric coding is performed on the third DC coefficient and the third AC coefficient to obtain a third picture file, excluding: the third DC coefficient and the third AC coefficient. Huffman encoding is performed on the third AC coefficient to obtain a picture file in JPEG format; Huffman decoding is performed on the picture file in JPEG format to obtain a fourth DC coefficient and a fourth AC coefficient; the fourth DC coefficient and the The fourth AC coefficient is subjected to arithmetic coding or asymmetric coding to obtain the third picture file.

The third aspect of the embodiments of the present application provides a computer device, which has a method for implementing the first aspect, the second aspect, any possible implementation manner of the first aspect, or any possible implementation manner of the second aspect. Function. This function can be implemented by hardware, or it can be implemented by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions.

The fourth aspect of the embodiment of the present application provides a computer device, which may include a memory, a processor, and a bus system. The memory is used to store programs, and the processor is used to call the program stored in the memory to execute the first aspect of the embodiment of the present application. Or any possible implementation method of the first aspect.

The fourth aspect of the embodiments of the present application provides a computer-readable storage medium. The computer-readable storage medium stores instructions. When run on a computer, the computer can execute the above-mentioned first aspect, second aspect, and first aspect. any possible implementation of the second aspect, or any possible implementation of the second aspect.

The fifth aspect of the embodiment of the present application provides a computer program that, when run on a computer, causes the computer to execute the first aspect, the second aspect, any of the possible implementation methods of the first aspect, or any of the second aspects. possible implementation methods.

The sixth aspect of the embodiment of the present application provides a chip. The chip (such as a CPU) includes at least one processor and at least one interface circuit. The interface circuit is coupled to the processor. The at least one interface circuit is used to perform a transceiver function. and sends the instructions to at least one processor. The at least one processor is used to run a computer program or instructions, which has the ability to implement the above-mentioned first aspect, the second aspect, any one of the possible implementation methods of the first aspect, or any one of the second aspect. This function can be implemented by hardware, software, or a combination of hardware and software. The hardware or software includes one or more modules corresponding to the above functions. In addition, the interface circuit is used to communicate with other modules outside the chip. For example, the interface circuit can send the dummy file and the second picture file obtained by the processor on the chip to the device on the other side for storage.

The second to sixth aspects of the embodiments of the present application can achieve the beneficial effects described in the first aspect. To avoid repetition, they will not be described again here.

Description of the drawings

Figure 1 is a storage system architecture diagram provided by an embodiment of the present application;

Figure 2 is a schematic flow chart of the image processing method provided by the embodiment of the present application;

Figure 3 is another schematic flowchart of the image processing method provided by the embodiment of the present application;

Figure 4 is another schematic flowchart of the image processing method provided by the embodiment of the present application;

Figure 5 is another schematic flow chart of the image processing method provided by the embodiment of the present application;

Figure 6 is another schematic flowchart of the image processing method provided by the embodiment of the present application;

Figure 7 is another schematic flowchart of the image processing method provided by the embodiment of the present application;

Figure 8 is another schematic flowchart of the image processing method provided by the embodiment of the present application;

Figure 9 is another schematic flowchart of the image processing method provided by the embodiment of the present application;

Figure 10 is a schematic structural diagram of a computer device provided by an embodiment of the present application;

Figure 11 is a schematic structural diagram of a computer device provided by an embodiment of the present application;

Figure 12 is a schematic structural diagram of a computer device provided by an embodiment of the present application.

Detailed ways

The embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention. In the following description, specific aspects of embodiments of the invention are shown or may be used in the accompanying drawings. It is to be understood that embodiments of the invention may be utilized in other aspects and may involve structural or logical changes not depicted in the drawings. Accordingly, the following detailed description is not to be taken in a limiting sense, and the scope of the invention is defined by the appended claims. For example, it should be understood that disclosure in connection with the described methods may equally apply to corresponding devices or systems for performing the methods, and vice versa. For example, if one or more specific method steps are described, the corresponding device may include one or more units, such as functional units, to perform the one or more described method steps (e.g., one unit performs one or more steps , or a plurality of units, each of which performs one or more of a plurality of steps), even if such unit or units are not explicitly depicted or illustrated in the drawings. On the other hand, for example, if a specific apparatus is described based on one or more units such as functional units, the corresponding method may include a step to perform the functionality of the one or more units (e.g., a step to perform the functionality of the one or more units) functionality, or a plurality of steps, each of which performs the functionality of one or more of a plurality of units), even if such one or more steps are not explicitly depicted or illustrated in the drawings. Further, it should be understood that features of various exemplary embodiments and/or aspects described herein may be combined with each other unless expressly stated otherwise.

In the embodiment of the present invention, "at least one" refers to one or more, and "multiple" refers to two or more. "And/or" describes the association of associated objects, indicating that there can be three relationships, for example, A and/or B, which can mean: A exists alone, A and B exist simultaneously, and B exists alone, where A, B can be singular or plural. The character "/" generally indicates that the related objects are in an "or" relationship. "At least one of the following" or similar expressions thereof refers to any combination of these items, including any combination of a single item (items) or a plurality of items (items). For example, at least one of a, b, or c can mean: a, b, c, a-b, a-c, b-c, or a-b-c, where a, b, c can be single or multiple .

The terms used in the embodiments of the present invention are only used to explain specific embodiments of the present invention and are not intended to limit the present invention.

First, the application scenarios involved in the image processing method provided by the embodiments of this application are introduced. In a possible implementation, the image processing method provided by the embodiment of the present application can be executed on the terminal side. For example, the end-side device can obtain the first picture file from its own memory or the cloud, and the end-side processor decodes and performs other processing operations on the first picture file, and finally obtains an RGB format picture file for display. In a possible implementation, the image processing method provided by the embodiment of the present application can be executed on the cloud side. For example, the cloud side device can obtain the first picture file from its own memory, and the cloud side processor decodes the first picture file and performs other processing operations to finally obtain the RGB format picture file, and then converts the RGB format image file into the RGB format picture file. The picture is sent to the client for display. In a possible implementation manner, the image processing method provided by the embodiment of the present application can be executed collaboratively through the device and cloud. For example, the cloud-side device can obtain the first image file from its own memory, perform certain processing, and then send the result of an intermediate process to the end-side device, which then performs subsequent processing and finally generates Picture files in RGB format are used for display. In a possible implementation, the image processing method provided by the embodiment of the present application can be applied to a home storage scenario. In this case, the home storage can correspond to the above-mentioned cloud storage. The method is similar and will not be described again.

Secondly, the system architecture provided by the embodiment of the present application is introduced. For details, please refer to Figure 1. Figure 1 is a storage system architecture diagram provided by the embodiment of the present invention. As shown in Figure 1, the storage system includes computing nodes 11, storage nodes 12 and storage media 13. Wherein, the computing node 11 and the storage node 12 may be physical servers, or may also be virtual machines, Containers and other virtual entities based on general hardware resource abstraction. The storage medium 13 is, for example, a storage medium such as a solid state disk (SSD), a hard disk drive (HDD), a storage class memory (SCM), etc., and the storage medium 13 may be a storage medium. The storage medium local to the node may also be a distributed storage medium connected to the storage node.

The computing node 11 can perform data access to the storage node 12, such as writing data, reading data, etc. Specifically, the computing node 11 may send a write request to the storage node 12 to write data. The data to be written in the write request may be, for example, various types of data such as pictures, databases, and texts. After receiving the write request, the storage node 12 may process the file involved in the write request through the encoding module 121, the decoding module 121, the processing module 123, etc. The encoding module 121, the pseudo file generation module 123, and the decoding module 122 may be in the form of software, hardware, or firmware.

In order to facilitate understanding, the terms involved in the embodiments of the present application are briefly introduced. Since the following encoding processes are all common encoding processes in the industry, the specific implementation methods will not be described again in the embodiments of the present application.

1. Encode once

One-time encoding in the embodiment of this application refers to the process of encoding an RGB format image file into an image file in a format such as JPEG format, PNG (Portable Network Graphics, PNG) format, or GIF (Graphics Interchange Format, GIF) format. One-time encoding The process can also be called primary compression. This process mainly includes processes such as YUV coding, Discrete Cosine Transform (DCT), quantization, and Huffman coding (Huffman). Each transformation process will be described in detail below. introduction. The embodiments of the present application do not limit the format of the picture file into which the RGB format picture file is encoded. In the embodiment of the present application, the encoding of the RGB format picture file into the JPEG format picture file is taken as an example to illustrate the one-time encoding process. .

2. Secondary encoding

One-time encoding in the embodiment of this application refers to the process of encoding image files in JPEG format, PNG format, or GIF format into image files in a format that requires smaller storage space. The embodiment of the present application does not limit the format of the twice-encoded image file. The image format may be the same as or different from the format of the once-encoded image file, but the storage space required is smaller than that of the once-encoded image file. In the embodiment of this application, secondary encoding of a picture file in JPEG format is taken as an example to explain the process of secondary encoding.

3.RGB

RGB color mode is a color standard in the industry. It is obtained by changing the three color channels of red (R, Red), green (G, Green), and blue (B, Blue) and the superposition of them. Of all kinds of colors, RGB represents the colors of the three channels of red, green, and blue. This standard includes almost all colors that human vision can perceive, and is one of the most widely used color systems. Picture files used for display in display scenarios are usually RGB format picture files.

4.YUV

YUV is a color encoding method. Often used in various video processing components. YUV takes into account human perception when encoding photos or videos, allowing for reduced chroma bandwidth. YUV is a type of compiled true-color color space (color space). Y'UV, YUV, YCbCr, YPbPr and other proper nouns can all be called YUV, and they overlap with each other. "Y" represents brightness (Luminance or Luma), which is the grayscale value. "U" and "V" represent chrominance (Chrominance or Chroma), which are used to describe the color and saturation of the image and are used to specify pixels. s color. YUV decoding is the reverse process corresponding to YUV encoding.

Since JPEG only supports the data structure of the YUV color mode and does not support the RGB image data structure, YUV encoding (data conversion of the color mode) is required before subsequent encoding of the RGB format image file.

5.DCT

DCT transformation is a process that transforms image signals in the frequency domain and separates high-frequency and low-frequency information. Then the high-frequency part of the image (ie, image details) is compressed to achieve the purpose of compressing the image data. First divide the image into multiple 8*8 matrices. Then perform DCT transformation on each matrix, and obtain a frequency coefficient matrix after transformation. The frequency coefficients in the frequency coefficient matrix are all floating point numbers. Inverse DCT is the inverse process corresponding to the DCT transform.

6.Quantification

Quantization Since the codebooks used in the subsequent encoding process are all integers, it is necessary to quantize the transformed frequency coefficients and convert them into integers. Inverse quantization is the reverse process corresponding to quantization.

7. Huffman coding

Huffman coding is a type of variable word length coding. This method is completely based on the probability of character occurrence to construct the codeword with the shortest average length of different prefixes. It is also called the best coding or Huffman coding. Huffman decoding is the inverse process corresponding to Huffman coding.

8. Arithmetic coding

Arithmetic coding is a lossless data compression method and an entropy coding method. The difference from other entropy coding methods is that other entropy coding methods usually divide the input message into symbols and then encode each symbol, while arithmetic coding directly encodes the entire input message into a number, which satisfies (0.0≤n<1.0) decimal n. Arithmetic coding can give near-optimal coding results given a set of symbols and symbol probabilities. Compression algorithms that use arithmetic coding usually estimate the probabilities of input symbols before encoding. The more accurate this estimate is, the closer the encoding result is to the optimal result. Arithmetic decoding is the reverse process corresponding to arithmetic encoding.

9. Asymmetric Numeral Systems (ANS) encoding

ANS coding is a lossless compression algorithm that has both the compression rate of the AC algorithm and the compression speed of the Huffman algorithm.

With the popularity of terminals represented by smartphones, the proportion of media files (especially pictures) in existing smartphones and cloud storage is generally high, and as camera pixels continue to increase, the resolution of pictures is getting higher and higher. Each photo also takes up more and more storage space. At present, insufficient storage space has become one of the main factors for users to change mobile phones. Reducing the storage space required for pictures and improving storage space usage efficiency can greatly improve user experience and stickiness. JPEG (joint photographic experts group, JPEG) is currently the most widely used picture standard (picture format). However, JPEG format picture files require a large storage space, and storing a large number of JPEG format pictures can easily lead to terminal or cloud storage Insufficient space problem.

Among the currently popular technologies, the system storage space is saved mainly by encoding image files in JPEG format into image files that require smaller storage space. For the existing standard JPEG, there are already standard decoders that implement various technologies from JPEG decoding to display. The image files obtained after further encoding the JPEG format image files are usually decoded into JPEG format first. After decoding the image file, use an existing standard decoder to decode the image file in JPEG format and use it in scenes such as display. The whole process is relatively rigid and cumbersome, with high system complexity and high resource overhead.

Specifically, please refer to Figure 2, which is a schematic flow chart of processing image files in the prior art. In the existing technology, as shown by the arrow on the left in Figure 2, first, the original RGB format image file is obtained through camera shooting or social software reception, and then the RGB format image file is converted into YUV through YUV encoding. format image files, then perform DCT transformation and quantization on the YUV format image files, convert the YUV format image files into DC coefficients and AC coefficients, and finally, convert the DC coefficients and AC coefficients into JPEG format images through Huffman coding document. The above process is a one-time encoding process for converting RGB image files into JPEG format image files (here it can be called a complete one-time encoding process).

Subsequently, in order to save storage space, the image file in JPEG format is re-encoded to obtain a re-encoded image file (the figure shows an image file in X format, where X format represents any possible image format). Specifically, Huffman decoding is first performed on the image file in JPEG format to obtain the tributary coefficients and AC coefficients, and then the DC coefficients and AC coefficients are encoded to obtain the image file after secondary encoding. The above process can be called a complete secondary encoding process. Finally, the storage space will store the image files after secondary encoding, instead of storing the original RGB format image files and the once-encoded JPEG format image files. Therefore, the efficiency of storage space usage is greatly improved. .

When the picture file needs to be used for display, it needs to be restored to an RGB format picture file through the process shown by the arrow on the right in Figure 2. Specifically, it is necessary to first decode the image file obtained after secondary encoding to obtain a JPEG format image file, and then decode the JPEG format image file to obtain an RGB format image file.

Specifically, in the process of decoding the image file obtained after secondary encoding to obtain the image file in JPEG format, first, the image file obtained after secondary encoding is decoded to obtain the DC coefficient and the AC coefficient, and then, the DC coefficient and the AC coefficient are obtained. Perform Huffman encoding to obtain image files in JPEG format. The above process can be called a complete secondary decoding process. In the process of decoding a JPEG format image file to obtain an RGB format image file, first, Huffman decoding is performed on the JPEG format image file to obtain DC coefficients and AC coefficients, and then, the DC coefficients and AC coefficients are inversely quantized and decoded. DCT transform to obtain an image file in YUV format. Finally, YUV decode the image file in YUV format to obtain an image file in RGB format. The above process can be called a complete decoding process. Picture files in RGB format can be used for display.

In the prior art, in the process of encoding an RGB image to obtain a twice-encoded image file, in order to obtain a JPEG format image file, a Huffman encoding is performed on the DC coefficients and AC coefficients. In order to obtain the DC coefficients and AC coefficients Coefficients, another Huffman decoding is performed to obtain the DC coefficients and AC coefficients. In fact, in scenarios where JPEG format image files are not required as intermediate output, the step of generating JPEG format image files can be skipped and X format image files can be obtained directly from RGB format image files by encoding.

Specifically, please refer to Figure 3, which is a schematic flow chart of a simplified image processing process. As shown in Figure 3, in the process of encoding RGB format image files, first, YUV encoding is performed on the RGB format image files to obtain YUV format image files, and then, the YUV format image files are subjected to DCT transformation and Quantize to obtain DC coefficients and AC coefficients. Finally, directly decode the DC coefficients and AC coefficients to obtain X format image files. The system can store image files in X format to improve storage space utilization efficiency. Correspondingly, in the process of decoding the X format picture file, first, the X format picture file is decoded to obtain the DC coefficients and AC coefficients, and then, the DC coefficients and AC coefficients are inverse quantized and inverse DCT transformed to obtain Obtain the picture file in YUV format. Finally, perform YUV decoding on the picture file in YUV format to obtain the picture file in RGB format. The picture file in RGB format can be used for display.

The picture processing flow shown in Figure 3 deletes the redundant Huffman encoding and Huffman decoding processes in the existing technology, and simplifies the primary encoding process, secondary encoding process, primary decoding process and secondary decoding process. By simplifying the decoding and encoding process, redundant operations can be avoided, resource overhead is reduced to a certain extent, and system complexity is reduced.

Based on the above background and inventive concept, the image processing method provided by the embodiment of the present application is introduced in detail. The image processing method corresponds to the steps on the right side of Figure 3, that is, decoding the file obtained by secondary encoding to The process of obtaining image files in RGB format for display. This image processing method can be used in various application scenarios mentioned above. Here, only the terminal side is used as the execution subject to describe the solution in detail. It should be understood that it can also be used in other application scenarios, and the method is basically the same. Please refer to Figure 4 for details. Figure 4 is a schematic flowchart of the image processing method provided by the embodiment of the present application. Specifically, it may include the following steps:

401. Obtain the first image file.

The first picture file here corresponds to the X-format picture file in FIG. 3 , that is, the stored picture file, and the first picture file may be stored in the memory. The embodiment of the present application does not limit the format of the first picture file, which may be a private format or a standard format.

In step 401, the first picture file can be obtained through a variety of possible implementation methods. In a possible implementation, the first picture file can be stored in a local storage. In this case, the first picture file can be obtained from the local storage. In another possible implementation, the first picture file can be stored in a cloud storage, and at this time, the first picture file can be received from the cloud. In another possible implementation, the first picture file can be stored in other electronic devices (for example, independent memory or other terminal devices). At this time, the first picture file can be received from other electronic devices.

The first image file may come from multiple sources. In a possible implementation, the first picture file can be obtained through the process shown by the arrow on the left in Figure 2, that is, the first picture file is obtained by performing a complete one-time encoding of the picture file in RGB format. It is obtained by obtaining image files in JPEG and other formats, and then performing complete secondary encoding on the image files in JPEG and other formats. In another possible implementation, the first picture file can be obtained through the process shown by the arrow on the left side of Figure 3, that is, the first picture file is a simplified one-time encoding of the RGB format picture file. It is obtained by obtaining image files in JPEG and other formats, and then performing simplified secondary encoding on the image files in JPEG and other formats. In another possible implementation, the first picture file can be obtained by encoding a picture file in a format such as JPEG. The embodiment of the present application does not limit the acquisition method of the picture file in a format such as JPEG. For example, The picture files in JPEG and other formats can be obtained through social software, etc., or obtained from the cloud.

It should be understood that the above-mentioned picture files in JPEG and other formats are not limited to JPEG format, and may also be common picture formats such as PNG format or GIF format that can be re-encoded. The embodiment of the present application only takes an image file in JPEG format as an example to describe the image processing method in detail.

402. Perform arithmetic decoding or asymmetric number system (ANS) decoding on the first picture file to obtain the first DC coefficient and the first AC coefficient.

403. Perform inverse quantization and inverse discrete cosine transform on the first DC coefficient and the first AC coefficient to obtain a picture file in YUV format.

It should be noted that in step 403, the first DC coefficient and the first AC coefficient obtained in step 402 are directly inverse quantized and inverse discrete cosine transformed to obtain a picture file in YUV format. Specifically, in the prior art, it is necessary to perform Huffman encoding on the first DC coefficient and the first AC coefficient obtained in step 402 to obtain a picture file in JPEG format, and then perform Huffman decoding on the picture file in JPEG format to obtain the second DC coefficient and second AC coefficient, and then perform inverse quantization and inverse discrete cosine transform on the second DC coefficient and second AC coefficient to obtain a picture file in YUV format. Step 403 is different from the solution in the prior art. It skips the Huffman encoding and Huffman decoding steps and directly performs inverse quantization and inverse discrete cosine transform on the first DC coefficient and the first AC coefficient obtained in step 402 to obtain a picture in YUV format. document.

404. Convert the YUV format image file into an RGB format image file.

Step 404 can be implemented through the YUV decoding process, and the resulting image file in RGB format can be used for display or for users to browse.

The above image processing method simplifies the redundant steps in the decoding process, makes the decoding process more flexible, reduces system complexity and resource overhead, and also improves the efficiency of image file decoding to a certain extent.

With the diversified development of terminal functions, users have many possible ways to use image files. Therefore, according to different usage methods, image files can be processed in different ways to maximize system processing efficiency. Please refer to Figure 5, which takes the first image file as a starting point. In one possible implementation, the user may wish to convert the A picture file is used for display and other scenes, and the first picture file needs to be converted into an RGB format picture file. At this time, the image processing method shown in Figure 4 can be used to convert the first image file into an RGB format image file through a simplified secondary decoding process and a simplified primary decoding process. In another possible implementation, the user may want to edit the first picture file, or send the first picture file through social applications such as WeChat and Weibo. The first picture file needs to be converted into a picture in a format such as JPEG. document. At this time, a complete secondary decoding process can be used to convert the first picture file into a picture file in a format such as JPEG.

It should be understood that the above application scenarios are only exemplary, and other application scenarios are also possible. For application scenarios that require image files in JPEG and other formats, a complete secondary decoding process can be used to process the first image file. For business-related scenarios that require image files in RGB format, simplified secondary decoding and simplified The first picture file is processed in one decoding process.

Adopting different processing methods for image files according to different uses can make the system's management of image files more flexible, further improve system efficiency, reduce system complexity, and improve resource utilization while ensuring the realization of functions.

Based on the above background and inventive concept, another image processing method provided by the embodiment of the present application will be introduced in detail. This image processing method corresponds to the steps on the left side in Figure 3, that is, processing the image file in RGB format. The process of encoding to obtain a secondary encoded file for storage. This image processing method can be used in various application scenarios mentioned above. Here, only the terminal side is used as the execution subject to describe the solution in detail. It should be understood that it can also be used in other application scenarios, and the method is basically the same. Please refer to Figure 6 for details. Figure 6 is a schematic flowchart of an image processing method provided by an embodiment of the present application. Specifically, it may include the following steps:

601. Obtain image files in RGB format.

The embodiments of this application do not limit the method of obtaining image files in RGB format. For example, image files in RGB format can be obtained through collection methods such as taking photos, or image files in RGB format can be received from the cloud or other electronic devices.

602. Convert the image file in RGB format into an image file in YUV format.

Step 602 may be implemented through a YUV encoding process.

603. Perform discrete cosine transformation and quantization on the YUV format image file to obtain the third DC coefficient and the third AC coefficient.

604. Perform arithmetic coding or asymmetric digital system coding on the third tributary coefficient and the third AC coefficient to obtain a third picture file. The third picture file is used for storage and memory.

After obtaining the third picture file, the third picture file can be stored. In one possible implementation, the third picture file can be stored in a local memory. In another possible implementation, The third picture file can be sent to the storage in the cloud for storage. In another possible implementation, the third picture file can be sent to other electronic devices for storage.

It should be noted that in step 604, arithmetic coding or asymmetric digital system coding is directly performed on the third DC coefficient and the third AC coefficient obtained in step 603 to obtain the third picture file. Specifically, in the prior art, it is necessary to perform Huffman encoding on the third DC coefficient and the third AC coefficient obtained in step 603 to obtain a picture file in JPEG format, and then perform Huffman decoding on the picture file in JPEG format to obtain the fourth DC coefficient. coefficient and the fourth AC coefficient, and then perform arithmetic coding or asymmetric digital system coding on the fourth DC coefficient and the fourth AC coefficient to obtain the third picture file. Step 604 is different from the solution in the prior art. It skips the Huffman encoding and Huffman decoding steps and directly performs arithmetic coding or asymmetric digital system coding on the third DC coefficient and the third AC coefficient obtained in step 603 to obtain the third picture file. .

Please refer to Figure 7. In a possible implementation, when the third image needs to be converted into an image file in a format such as RGB, the above image processing method also includes the following steps:

605. Perform arithmetic decoding or asymmetric digital system decoding on the third picture file to obtain the third DC coefficient and the third AC coefficient.

606. Perform inverse quantization and inverse discrete cosine transform on the third DC coefficient and the third AC coefficient to obtain a picture file in YUV format.

607. Convert the YUV format image file into an RGB format image file.

Steps 605-607 are optional. The specific implementation methods of steps 605-607 are basically the same as the implementation methods of steps 402-403. To avoid duplication, they will not be described again here.

For example, the scenarios in which the third image file needs to be converted into an image file in an RGB or other format include display, etc. Other scenarios that require the use of an image file in an RGB or other format are also possible.

Please refer to Figure 8. In a possible implementation, when the third picture needs to be converted into a picture file in a format such as JPEG, the above picture processing method also includes the following steps:

608. Perform arithmetic decoding or asymmetric digital system decoding on the third picture file to obtain the third DC coefficient and the third AC coefficient.

609. Perform Huffman encoding on the third DC coefficient and the third AC coefficient to obtain a picture file in JPEG format.

Steps 608 and 609 are optional. The specific implementation method of step 608 is basically the same as the implementation method of step 402. Step 609 can be implemented by solutions in the prior art. To avoid repetition, no details will be described here.

For example, the scenarios in which the third picture file needs to be converted into a picture file in a format such as JPEG include editing, sending through social applications such as WeChat and Weibo, etc. Other scenarios in which picture files in a format such as JPEG are also possible. .

The above image processing method simplifies the redundant steps in the encoding process, makes the encoding process more flexible, reduces system complexity and resource overhead, and also improves the efficiency of image file encoding to a certain extent.

With the diversified development of terminal functions, users have many possible ways to use image files. Therefore, according to different usage methods, image files can be processed in different ways to maximize system processing efficiency. Please refer to Figure 9, which uses an image file in RGB format as a starting point. In a possible implementation, the user may want to store the image file. At this time, in order to save storage space, the RGB format image file needs to be encoded into an X format image file that requires smaller storage space. At this time, the image processing method shown in Figure 6 can be used to convert the RGB format image file into an X format image file through a simplified primary encoding process and a simplified secondary encoding process. In another possible implementation, the user may want to edit the image file in RGB format, or send the image file through social applications such as WeChat and Weibo. In this case, the image file in RGB format needs to be converted into JPEG. Picture files in other formats. At this point, a complete one-pass encoding process can be used.

On the basis of the above corresponding embodiments, in order to better implement the above solutions of the embodiments of the present application, computer equipment for implementing the above solutions is also provided below. The computer device may include handheld terminal devices, such as mobile phones, computers, iPads, etc., and may also include smart wearable devices, such as smart bracelets, smart watches, smart heart rate meters, etc.; it may also include wheeled mobile devices, such as, Vehicles (such as self-driving vehicles), aircraft, robots (such as sweeping robots), etc. Specifically, this application does not limit the product form of computer equipment, as long as it can be used to implement the image processing method described in this application. All equipment can be called computer equipment.

Please refer to Figure 10. Figure 10 is a schematic structural diagram of a computer device provided by an embodiment of the present application. The computer device 1000 includes: an acquisition module 1003, a decoding module 1002 and a processing module 1002. The acquisition module 1001 is used to acquire the third A picture file; the decoding module 1002 is used to perform arithmetic decoding or ANS decoding on the first picture file to obtain the first DC coefficient and the first AC coefficient; the processing module 1003 is used to perform the first DC coefficient and the first AC coefficient The first AC coefficient is inversely quantized and inversely discrete cosine transformed to obtain an image file in YUV format; the processing module is also used to convert the image file in YUV format into an image file in RGB format.

In a possible design, the first picture file is obtained by encoding the second picture file. The format of the first picture file is different from the format of the second picture file. The format of the second picture file is as follows Either:

JPEG format, PNG format or GIF format.

In a possible design, the first picture file is stored in the memory.

In a possible design, the image file in RGB format is used for display

In one possible design, the acquisition module 1001 is specifically configured to receive the first picture file from the cloud or other electronic devices.

In a possible design, the processing module is not used to: perform Huffman coding on the first DC coefficient and the first AC coefficient to obtain a picture file in JPEG format; perform Huffman coding on the picture file in JPEG format. Mann decoding is performed to obtain the second DC coefficient and the second AC coefficient; the second DC coefficient and the second AC coefficient are inversely quantized and inversely discrete cosine transformed to obtain a picture file in YUV format.

Please refer to Figure 11. Figure 11 is a schematic structural diagram of a computer device provided by an embodiment of the present application. The computer device 1100 includes: an acquisition module 1101, an encoding/decoding module 1102, and a processing module 1103. The acquisition module 1101 is used to Obtain a picture file in RGB format; the processing module 1103 is used to convert the picture file in RGB format into a picture file in YUV format; the processing module 1103 is also used to perform discrete cosine transformation and quantization on the picture file in YUV format to Obtain the third DC coefficient and the third AC coefficient; the encoding/decoding module 1102 is used to perform arithmetic coding or asymmetric digital system coding on the third DC coefficient and the third AC coefficient to obtain a third picture file. Three picture files are used for storage in memory.

In a possible design, the encoding/decoding module 1102 is also used to perform arithmetic decoding or asymmetric decoding on the third picture file to obtain the third DC coefficient or the third AC coefficient; the processing module 1103 is also used to Perform inverse quantization and inverse discrete cosine transform on the third DC coefficient or the third AC coefficient to obtain the image file in YUV format; the processing module 1103 is also used to convert the image file in YUV format into an image file in RGB format.

In a possible design, the encoding/decoding module 1102 is also used to perform arithmetic decoding or asymmetric decoding on the third picture file to obtain the third DC coefficient or the third AC coefficient; the encoding/decoding module 1102, It is also used to perform Huffman encoding on the third DC coefficient or the third AC coefficient to obtain a picture file in JPEG format.

In a possible design, the computer device 1100 also includes a sending module 1104 for sending the picture file to the cloud or other electronic devices for storage.

In one possible design, the encoding/decoding module 1102 is not used to perform Huffman encoding on the third DC coefficient and the third AC coefficient to obtain the image file in JPEG format; it performs Huffman encoding on the image file in JPEG format. Furman decoding is performed to obtain a fourth DC coefficient and a fourth AC coefficient; arithmetic coding or asymmetric coding is performed on the fourth DC coefficient and the fourth AC coefficient to obtain a third picture file.

The embodiment of the present application also provides a computer device. Please refer to Figure 12. Figure 12 is a schematic structural diagram of the computer device provided by the embodiment of the present application. For convenience of explanation, only the parts related to the embodiment of the present application are shown. If the specific technical details are not disclosed, please refer to the method section of the embodiments of this application. The computer device 1200 may be deployed with a pair of FIGS. 10 and 11 The modules described in the embodiments are used to implement the functions of the computer device 1000 in the embodiment corresponding to FIG. 10 and the functions of the computer device 1100 in the embodiment corresponding to FIG. 11 . Specifically, the computer device 1200 is implemented by one or more servers. The computer device 1200 may vary greatly due to different configurations or performance, and may include one or more central processing units (CPU) 1222 and memory 1232 , one or more storage media 1230 (eg, one or more mass storage devices) that store applications 1242 or data 1244. Among them, the memory 1232 and the storage medium 1230 may be short-term storage or persistent storage. The program stored in the storage medium 1230 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations on the computer device 1200 . Furthermore, the central processor 1222 may be configured to communicate with the storage medium 1230 and execute a series of instruction operations in the storage medium 1230 on the computer device 1200 .

Computer device 1200 may also include one or more power supplies 1226, one or more wired or wireless network interfaces 1250, one or more input and output interfaces 1258, and/or, one or more operating systems 1241, such as Windows Server™, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM and more.

In this embodiment of the present application, the central processor 1222 is used to execute the image processing method in the corresponding embodiments of FIG. 4 and FIG. 6 . For example, the central processor 1222 may be used to: obtain a first picture file; perform arithmetic decoding or asymmetric digital system decoding on the first picture file to obtain the first DC coefficient and the first AC coefficient; The coefficients and the first AC coefficient are inverse quantized and inverse discrete cosine transformed to obtain a YUV format image file; the YUV format image file is converted into an RGB format image file. For another example, the central processor 1222 can also be used to: obtain an image file in RGB format; convert the image file in RGB format into an image file in YUV format; perform discrete cosine transformation and quantization on the image file in YUV format to obtain The third DC coefficient and the third AC coefficient; perform arithmetic coding or asymmetric digital system coding on the third DC coefficient and the third AC coefficient to obtain a third picture file, and the third picture file is used for storage in the memory .

It should be noted that the central processing unit 1222 can also be used to execute any step in the method embodiment corresponding to Figure 4 and Figure 6 in this application. For specific content, please refer to the description in the method embodiment shown above in this application. No further details will be given here.

The image processing device provided by the embodiment of the present application may be a chip. The chip includes: a processing unit and a communication unit. The processing unit may be, for example, a processor. The communication unit may be, for example, an input/output interface, a pin, or a circuit. The processing unit can execute computer execution instructions stored in the storage unit, so that the chip executes the method described in the embodiments shown in FIG. 4 and FIG. 6 . Optionally, the storage unit is a storage unit within the chip, such as a register, cache, etc. The storage unit may also be a storage unit located outside the chip in the wireless access device, such as Read-only memory (ROM) or other types of static storage devices that can store static information and instructions, random access memory (random access memory, RAM), etc.

The embodiments of the present application also provide a computer-readable storage medium, which stores a program for signal processing. When it is run on a computer, it causes the computer to execute the steps described in the foregoing embodiments. The steps performed by computer equipment.

In addition, it should be noted that the device embodiments described above are only illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physically separate. The physical unit can be located in one place, or it can be distributed across multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, in the drawings of the device embodiments provided in this application, the connection relationship between modules indicates that there are communication connections between them, which can be specifically implemented as one or more communication buses or signal lines.

Through the above description of the embodiments, those skilled in the art can clearly understand that the present application can be implemented by software plus necessary general hardware. Of course, it can also be implemented by dedicated hardware including dedicated integrated circuits, dedicated CPUs, Special memory, special components, etc. can be implemented. In general, all functions performed by computer programs can be easily implemented with corresponding hardware. Moreover, the specific hardware structures used to implement the same function can also be diverse, such as analog circuits, digital circuits or special-purpose circuits. circuit etc. However, for this application, software program implementation is a better implementation in most cases. Based on this understanding, the technical solution of the present application can be embodied in the form of a software product in essence or that contributes to the existing technology. The computer software product is stored in a readable storage medium, such as a computer floppy disk. , U disk, mobile hard disk, read only memory (ROM), random access memory (RAM), magnetic disk or optical disk, etc., including several instructions to make a computer device (which can be a personal computer, training equipment, or network equipment, etc.) to execute the methods described in various embodiments of this application.

In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it may be implemented in whole or in part in the form of a computer program product.

The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, the computer instructions may be transferred from a website, computer, training device, or data The center transmits to another website site, computer, training equipment or data center through wired (such as coaxial cable, optical fiber, digital subscriber line) or wireless (such as infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store, or a data storage device such as a training device or a data center integrated with one or more available media. The usable media may be magnetic media (eg, floppy disks, hard disks, magnetic tapes), optical media (eg, high-density digital video discs (DVD)), or semiconductor media (eg, solid state disks). ,SSD)), etc.

Claims

An image processing method, characterized by including:

Get the first image file;

Perform arithmetic decoding or asymmetric digital system decoding on the first picture file to obtain the first DC coefficient and the first AC coefficient;

Perform inverse quantization and inverse discrete cosine transform on the first DC coefficient and the first AC coefficient to obtain a picture file in YUV format;

Convert the image file in YUV format into an image file in RGB format.
The method of claim 1, wherein the first picture file is obtained by encoding a second picture file, and the format of the first picture file is different from the format of the second picture file, so The image format of the second image file is any of the following:

JPEG format, PNG format or GIF format.
The method according to claim 1 or 2, characterized in that the first picture file is stored in a memory.
The method according to any one of claims 1 to 3, characterized in that the picture file in RGB format is used for display.
The method according to any one of claims 1-4, characterized in that said obtaining the first picture file includes:

Receive the first picture file from the cloud or other electronic device.
The method according to any one of claims 1 to 5, characterized in that: performing inverse quantization and inverse discrete cosine transform on the first DC coefficient and the first AC coefficient to obtain a picture file in YUV format , excluding:

Perform Huffman coding on the first DC coefficient and the first AC coefficient to obtain a picture file in JPEG format;

Perform Huffman decoding on the picture file in JPEG format to obtain the second DC coefficient and the second AC coefficient;

Perform inverse quantization and inverse discrete cosine transform on the second DC coefficient and the second AC coefficient to obtain a picture file in YUV format.
An image processing method, characterized by including:

Get image files in RGB format;

Convert the image file in RGB format into an image file in YUV format;

Perform discrete cosine transformation and quantization on the picture file in YUV format to obtain the third DC coefficient and the third AC coefficient;

Arithmetic coding or asymmetric digital system coding is performed on the third DC coefficient and the third AC coefficient to obtain a third picture file, and the third picture file is used for storage in a memory.
The method of claim 7, further comprising:

Perform arithmetic decoding or asymmetric decoding on the third picture file to obtain the third DC coefficient or the third AC coefficient;

Perform inverse quantization and inverse discrete cosine transform on the third DC coefficient or the third AC coefficient to obtain the YUV grid image file;

Convert the image file in YUV format into an image file in RGB format.
The method of claim 7, further comprising:

Perform arithmetic decoding or asymmetric decoding on the third picture file to obtain the third DC coefficient or the third AC coefficient;

Huffman encoding is performed on the third DC coefficient or the third AC coefficient to obtain a picture file in JPEG format.
The method according to any one of claims 7-9, characterized in that the method further includes:

Send the third picture file to the cloud or other electronic device for storage.
The method according to any one of claims 7-10, characterized in that the third DC coefficient and the third AC coefficient are subjected to arithmetic coding or asymmetric coding to obtain a third picture file. include:

Perform Huffman coding on the third DC coefficient and the third AC coefficient to obtain a picture file in JPEG format;

Perform Huffman decoding on the picture file in JPEG format to obtain the fourth DC coefficient and the fourth AC coefficient;

Arithmetic coding or asymmetric coding is performed on the fourth DC coefficient and the fourth AC coefficient to obtain a third picture file.
A computer device, characterized in that it includes:

Acquisition module, used to obtain the first image file;

A decoding module configured to perform arithmetic decoding or asymmetric digital system decoding on the first picture file to obtain the first DC coefficient and the first AC coefficient;

A processing module configured to perform inverse quantization and inverse discrete cosine transform on the first DC coefficient and the first AC coefficient to obtain a picture file in YUV format;

The processing module is also used to convert the picture file in YUV format into a picture file in RGB format.
The device according to claim 12, wherein the first picture file is obtained by encoding a second picture file, and the format of the first picture file is different from the format of the second picture file, so The format of the second picture file is any of the following:

JPEG format, PNG format or GIF format.
The device according to claim 12 or 13, characterized in that the first picture file is stored in a memory.
The device according to any one of claims 12-13, characterized in that: the picture file in RGB format is used for display.
The device according to any one of claims 12-15, characterized in that the processing module is not used for:

Perform Huffman coding on the first DC coefficient and the first AC coefficient to obtain a picture file in JPEG format;

Perform Huffman decoding on the picture file in JPEG format to obtain the second DC coefficient and the second AC coefficient;

Perform inverse quantization and inverse discrete cosine transform on the second DC coefficient and the second AC coefficient to obtain the YUV grid image file.
A computer device, characterized in that it includes:

Acquisition module, used to obtain image files in RGB format;

A processing module, used to convert the image files in RGB format into image files in YUV format;

The processing module is also used to perform discrete cosine transform and quantization on the picture file in YUV format to obtain the third DC coefficient and the third AC coefficient;

A coding module, configured to perform arithmetic coding or asymmetric digital system coding on the third DC coefficient and the third AC coefficient to obtain a third picture file, where the third picture file is used for storage in a memory.
The device of claim 17, wherein the computing device further includes:

A decoding module configured to perform arithmetic decoding or asymmetric decoding on the third picture file to obtain the third DC coefficient or the third AC coefficient;

The processing module is also configured to perform inverse quantization and inverse discrete cosine transform on the third DC coefficient or the third AC coefficient to obtain the picture file in the YUV format;

The processing module is also used to convert the picture file in YUV format into a picture file in RGB format.
The device of claim 17, wherein the computing device further includes:

A decoding module configured to perform arithmetic decoding or asymmetric decoding on the third picture file to obtain the third DC coefficient or the third AC coefficient;

The encoding module is also configured to perform Huffman encoding on the third DC coefficient or the third AC coefficient to obtain a picture file in JPEG format.
The device according to any one of claims 17-19, characterized in that the encoding module is not used for:

Perform Huffman coding on the third DC coefficient and the third AC coefficient to obtain a picture file in JPEG format;

Perform Huffman decoding on the picture file in JPEG format to obtain the fourth DC coefficient and the fourth AC coefficient;

Arithmetic coding or asymmetric coding is performed on the fourth DC coefficient and the fourth AC coefficient to obtain a third picture file.
A computer device including a processor and a memory, the processor being coupled to the memory, characterized in that:

The memory is used to store programs;

The processor is configured to execute the program in the memory, so that the computer device executes the method according to any one of claims 1-6 or 7-11.
A computer-readable storage medium includes a program that, when run on a computer, causes the computer to perform the method according to any one of claims 1-6 or 7-11.
A computer program product containing instructions that, when run on a computer, cause the computer to perform the method according to any one of claims 1-6 or 7-11.