WO2013155880A1 - 图像压缩方法和装置 - Google Patents

图像压缩方法和装置 Download PDF

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Publication number
WO2013155880A1
WO2013155880A1 PCT/CN2013/070049 CN2013070049W WO2013155880A1 WO 2013155880 A1 WO2013155880 A1 WO 2013155880A1 CN 2013070049 W CN2013070049 W CN 2013070049W WO 2013155880 A1 WO2013155880 A1 WO 2013155880A1
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image
specific area
area
compression
specific
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PCT/CN2013/070049
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English (en)
French (fr)
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祁云飞
龚铮
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华为终端有限公司
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Publication of WO2013155880A1 publication Critical patent/WO2013155880A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
    • H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
    • H04N21/234—Processing of video elementary streams, e.g. splicing of video streams, manipulating MPEG-4 scene graphs
    • H04N21/2343—Processing of video elementary streams, e.g. splicing of video streams, manipulating MPEG-4 scene graphs involving reformatting operations of video signals for distribution or compliance with end-user requests or end-user device requirements
    • H04N21/234327—Processing of video elementary streams, e.g. splicing of video streams, manipulating MPEG-4 scene graphs involving reformatting operations of video signals for distribution or compliance with end-user requests or end-user device requirements by decomposing into layers, e.g. base layer and one or more enhancement layers
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/115—Selection of the code volume for a coding unit prior to coding
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/146—Data rate or code amount at the encoder output
    • H04N19/152—Data rate or code amount at the encoder output by measuring the fullness of the transmission buffer
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/164—Feedback from the receiver or from the transmission channel
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/167—Position within a video image, e.g. region of interest [ROI]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H04N19/172—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a picture, frame or field
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
    • H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
    • H04N21/234—Processing of video elementary streams, e.g. splicing of video streams, manipulating MPEG-4 scene graphs
    • H04N21/2343—Processing of video elementary streams, e.g. splicing of video streams, manipulating MPEG-4 scene graphs involving reformatting operations of video signals for distribution or compliance with end-user requests or end-user device requirements
    • H04N21/234345—Processing of video elementary streams, e.g. splicing of video streams, manipulating MPEG-4 scene graphs involving reformatting operations of video signals for distribution or compliance with end-user requests or end-user device requirements the reformatting operation being performed only on part of the stream, e.g. a region of the image or a time segment
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/60—Network structure or processes for video distribution between server and client or between remote clients; Control signalling between clients, server and network components; Transmission of management data between server and client, e.g. sending from server to client commands for recording incoming content stream; Communication details between server and client 
    • H04N21/63—Control signaling related to video distribution between client, server and network components; Network processes for video distribution between server and clients or between remote clients, e.g. transmitting basic layer and enhancement layers over different transmission paths, setting up a peer-to-peer communication via Internet between remote STB's; Communication protocols; Addressing
    • H04N21/647—Control signaling between network components and server or clients; Network processes for video distribution between server and clients, e.g. controlling the quality of the video stream, by dropping packets, protecting content from unauthorised alteration within the network, monitoring of network load, bridging between two different networks, e.g. between IP and wireless
    • H04N21/64723—Monitoring of network processes or resources, e.g. monitoring of network load
    • H04N21/64738—Monitoring network characteristics, e.g. bandwidth, congestion level
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N7/00—Television systems
    • H04N7/14—Systems for two-way working

Definitions

  • the present invention relates to the field of image processing, and in particular, to an image compression method and apparatus. Background technique
  • the fluency of the video call and the clarity of the video are two key metrics for measuring the quality of the video call. Especially when the communication load is very large, it is very difficult to ensure the smoothness of the call of the video call and to make the image clear.
  • the general approach to image processing is to greatly reduce the resolution of the image.
  • the specific implementation is: first, by analyzing the traffic of the data link layer in the video call or the strength of the signal, and then reducing the resolution of the image according to the size of the traffic and the degree of interference of the video signal, so as to reduce the network transmission.
  • the amount of data in a single frame image ensures the smoothness of real-time transmission of video signals.
  • the embodiment of the invention provides an image compression method and device, so as to ensure the clarity of a specific area while ensuring a certain fluency while the data transmission environment is poor during a video call.
  • the present invention provides an image compression method, the method comprising: detecting a network congestion degree of an image transmission network;
  • the present invention provides an image compression apparatus, where the apparatus includes: a detecting unit, configured to detect a network congestion degree of an image transmission network;
  • a first calculating unit configured to calculate an available transmission rate of the transmission network transmission image according to the network congestion degree
  • a second calculating unit configured to calculate, according to the available transmission rate, a data amount threshold of the transmission network transmission single frame image
  • An identifying unit configured to identify a specific area and a non-specific area in the image when a data amount of the image transmitted is greater than a data amount threshold of the single frame image
  • a compression unit configured to compress a specific area and a non-specific area in the image according to different compression ratios.
  • An image compression method and apparatus provided by an embodiment of the present invention, by detecting a network of an image transmission network
  • FIG. 1 is a schematic diagram of an image compression method according to an embodiment of the present invention.
  • FIG. 2 is a flowchart of an image compression method according to Embodiment 2 of the present invention.
  • FIG. 3 is a flowchart of a third image compression method according to Embodiment 3 of the present invention.
  • FIG. 4 is a flowchart of a fourth image compression method according to an embodiment of the present invention.
  • FIG. 5 is a flowchart of an image compression method according to Embodiment 5 of the present invention.
  • FIG. 6 is a flowchart of an image compression method according to Embodiment 6 of the present invention.
  • FIG. 7 is a schematic diagram of an image compression apparatus according to Embodiment 7 of the present invention.
  • FIG. 8 is a schematic diagram of an image compression apparatus according to Embodiment 8 of the present invention. Concrete itt
  • FIG. 1 is a schematic diagram of an image compression method according to an embodiment of the present invention, wherein a specific area is described by taking a face area as an example.
  • the present embodiment includes an original image 11, an image 12 that identifies a face region, a face region 13, a non-specific region 14, a compressed face region 15, a compressed non-specific region 16, and a complete The compressed image 17.
  • the original image includes both the user-specified area and the specific area, and the area other than the deducted area, that is, the non-specific area, for example, the face area in the original image 11 is a specific area, and the original image is deducted from the face area.
  • the remaining other areas are non-specific areas.
  • the face area in 11 is the image 12 of the face area, and after the face area 1 3 is recognized, the other areas of the image are the non-specific area 14, and the face area 1 3 and the non-specific area are compressed according to different compression ratios. 14 is compressed to obtain a compressed face region 15 and a compressed non-specific region 16, and the compressed face region 15 and the compressed non-specific region 16 constitute a complete compressed image 17.
  • the image 12 that recognizes the specific region may be first divided into the face region 13 and the non-specific region 14 by image segmentation technology, and then the face region 13 and the non-specific region are processed according to different compression ratios by image compression technology. 14 compresses to obtain the compressed face region 15 and the compressed non-specific region 16, and again synthesizes the compressed face region 15 and the compressed non-specific region 16 into a complete compressed image by image synthesis technology. 17.
  • FIG. 2 is a flowchart of an image compression method according to Embodiment 2 of the present invention. As shown in the figure, the embodiment specifically includes the following steps:
  • Step 21 0 The network congestion degree of the image transmission network is detected through a feedback mechanism, and the specific parameters include a packet loss rate, an average queue length, a number of packets retransmitted over time, and an average packet delay.
  • Step 220 Calculate an available transmission rate of the transmission network transmission image according to the network congestion degree.
  • the higher the network congestion the smaller the available transmission rate; conversely, the lower the network congestion, the larger the available transmission rate.
  • Step 230 Calculate a data volume threshold of the transmission network transmission single frame image according to the available transmission rate, that is, calculate a size limit of the single frame image according to the available transmission rate.
  • the smoothness of real-time image transmission is guaranteed only if the image of each frame that needs to be transmitted is less than or equal to the size limit of a single-frame image.
  • Step 240 Determine whether the data amount of the transmitted image is greater than a data amount threshold of the single frame image. Specifically, if it is desired to ensure the smoothness of real-time image transmission, it is necessary to compare each frame image of the image with the data amount threshold of the single-frame image calculated according to the network congestion degree. If the image of each frame of the image is less than or equal to the data threshold of the single frame image, it indicates that the network congestion degree at this time is very low, which is a normal value, and the image clarity cannot be guaranteed without compressing the image. In time, the original image is directly transmitted in step 250.
  • the network congestion degree is high at this time, which is an abnormal value, and the image needs to be compressed.
  • the resolution of the partial area of the image is preferentially ensured, and then the process proceeds to step 260.
  • Step 250 When it is determined that each frame image of the image is less than or equal to a data volume threshold of the single frame image, it indicates that the network congestion degree at this time is very low, and belongs to a normal value, and the video call is not required to be compressed to ensure the clarity of the video call. Degree and real-time, the original image is transmitted directly.
  • Step 260 When the data amount of the transmitted image is greater than the data amount threshold of the single frame image, receive an instruction of the user specified area and determine a specific area of the image.
  • the specific area of the image may be a face area, or may be any area specified by the user, and the non-specific area of the image is an area other than the area designated by the user.
  • the user can specify any area in the image as a specific area.
  • users can specify multiple specific areas. For example, in a specific object in an image that needs to maintain sharpness, the user can specify that the specific things are specific areas. The other areas in the image after deducting a specific area are non-specific areas. In this way, it is convenient for the user to specify a certain area or certain areas, so that when the data transmission environment is poor, priority is given to the clarity of one or some areas while ensuring a certain degree of fluency.
  • Step 270 identifying a specific area and a non-specific area in the image by using a face recognition technology.
  • the face area of the image in the video stream is identified by the face recognition technology, and the image is divided into a face area and a non-specific area.
  • the technique of dividing an image into a face area and a non-specific area can identify the face area of the image by face recognition technology, and the other areas of the image are non-specific areas, or the face area of the image is recognized, and then the image segmentation technique is adopted.
  • the image is divided into a face area and a non-specific area.
  • step 280 the specific area and the non-specific area in the image are compressed according to different compression ratios.
  • the specific area may be a face area
  • the non-specific area is a deduction of the face area. Area.
  • the compression ratio of the face region of the image and the non-specific region i or respectively is calculated according to the data amount threshold of the single frame image.
  • the first compression ratio rl of the face region of the image is 100%
  • the second compression ratio r2 of the non-specific region of the image is the data amount.
  • the above-mentioned face area and non-specific area of the image are compressed with different compression ratios.
  • the non-specific area of the image is preferentially compressed.
  • the non-specific area of the image is compressed without compressing the face area of the image.
  • the compressed image is an image with a clear face and a relatively blurred background.
  • the non-specific area of the image is compressed to the limit, and the image is not guaranteed to be smooth.
  • the face area of the image is also compressed, and the compressed image is the face. An image with a relatively clear area and a very blurred background.
  • step 270 in Fig. 2 will be described in detail below with reference to Figs. 3, 4, 5 and 6.
  • FIG. 3 is a flowchart of a third image compression method according to an embodiment of the present invention.
  • the process of compressing a specific area and a non-specific area in an image according to different compression ratios in the embodiment specifically includes the following steps: Step 301: A specific area of the image is a face area, and the non-specific area is an area other than the face area. Get the amount of data in the face area and the amount of data in the non-specific area.
  • the image data includes face area data and data of a non-specific area.
  • Step 302 Compare whether the data volume of the face area is smaller than the data quantity threshold of the network transmission single frame image. When the data volume of the face area is smaller than the data quantity threshold of the network transmission single frame image, it is ensured that only the non-specific area is compressed.
  • the fluency of the real-time image transmission so as to ensure the clarity of the face region, proceed to step 303; when the amount of data in the face region is smaller than the data amount of the single-frame image transmitted by the network, it means that only the non-specific region can not be compressed after compression.
  • step 305 is performed.
  • Step 303 When the amount of the face area data is smaller than the data quantity threshold of the network transmission single frame image, calculate the first compression ratio rl of the face area and the second compression ratio r2 of the non-specific area, and the specific calculation method is as shown in formula (1). And formula (1).
  • Step 304 compress the face region and the non-specific region by using the first compression ratio r l of the calculated face region and the second compression ratio Rr 2 of the non-specific region, respectively. That is, the non-specific area of the image is preferentially compressed without compressing the face area of the image.
  • the first compression ratio r l of the face region is larger than the second compression ratio r2 of the non-specific region.
  • the non-specific area of the image is preferentially compressed, and the compressed image is an image with a clear face and a relatively blurred background.
  • Step 305 When the amount of the face area data is not less than the data quantity threshold of the network transmission single frame image, calculate the first compression ratio rl of the face area and the second compression ratio r2 of the non-specific area, and the specific calculation method is as shown in the formula (3). ) and formula (4).
  • Step 306 compress the face region and the non-specific region by using the calculated first compression ratio rl of the face region and the second compression ratio r2 of the non-specific region. That is, the data of the non-specific area is no longer transmitted, and only the compressed face image is transmitted.
  • the first compression ratio rl of the face region is greater than the second compression ratio r 2 of the non-specific region.
  • the compressed image at this time is a relatively clear image of the face area.
  • there are many ways to calculate the compression ratio except that the compression ratios are calculated using equations (1), (2), (3), and ( 4 ), and other methods for calculating the compression ratio are included, and are not listed here.
  • the compression method calculates the compression ratio of the face region and the non-specific region according to the data amount of the acquired face region, the data amount of the non-specific region, and the data amount threshold of the network transmission single frame image, and then uses the calculated face region and When the non-specific area is compressed, when the data volume threshold of the single-frame image is changed by the network, the compression ratio of the face area and the non-specific area also changes, which ensures that the user receives the resolution of the specific area of the image while ensuring the clarity of the image. A certain degree of fluency.
  • FIG. 4 is a flowchart of a fourth image compression method according to an embodiment of the present invention. As shown in the figure, the process of compressing a specific area and a non-specific area in an image according to different compression ratios in the present embodiment includes the following steps:
  • Step 401 A specific area of the image is a face area, and the non-specific area is an area other than the face area.
  • a first compression ratio is preset to a non-specific area of the image, and a second compression ratio is preset to the face area of the image.
  • Step 402 compress a non-specific area of the image by using a preset first compression ratio, and compress the face area of the image by using a preset second compression ratio.
  • FIG. 5 is a flowchart of an image compression method according to Embodiment 5 of the present invention. As shown in the figure, the process of compressing and transmitting a specific area and a non-specific area in an image according to different compression ratios includes the following steps:
  • Step 501 A specific area of the image is a face area, and the non-specific area is an area other than the face area.
  • the image segmentation technique is used to segment the image into a face region and a non-specific region.
  • Steps 502 to 507 are the same as steps 301 to 306 in FIG. 3 and will not be described in detail herein.
  • Step 508 Synthesize the compressed face region and the compressed non-specific region by using image synthesis technology.
  • FIG. 6 is a flowchart of an image compression method according to Embodiment 6 of the present invention. As shown in the figure, the process of compressing and transmitting the specific area and the non-specific area in the image according to different compression ratios in the embodiment includes the following steps:
  • Step 601 A specific area of the image is a face area, and a non-specific area is an area other than the face area.
  • the image segmentation technique is used to segment the image into a face region and a non-specific region.
  • Step 603 compress the face region of the image by using a preset first compression ratio, and compress the non-specific image by using the preset second compression ratio.
  • Step 604 Combine the compressed face region and the compressed non-specific region into a complete image by using image synthesis technology.
  • a specific implementation process of compressing a specific area and a non-specific area in the image in accordance with different compression ratios in step 270 of Fig. 2 is described in detail with reference to Figs. 3, 4, 5 and 6.
  • the specific area is a face area
  • the non-specific area is an area other than the face area.
  • Figures 3, 4, 5, and 6 describe four different working processes, which have the same points and differences.
  • the compression ratio of the face area and the non-specific area of the image in FIG. 3 is determined according to the network congestion degree and calculated by the method, and the non-specific area is preferentially compressed, and the face area is compressed in the case of the non-specific area compression limit.
  • the compression ratio of the face area and the non-specific area of the image in FIG. 4 is determined by a preset manner; the compression ratio of the face area and the non-specific area except the image in FIG. 5 is calculated according to the network congestion degree and is calculated.
  • the image segmentation technique is used to divide the face region and the non-specific region of the image.
  • the image is synthesized by image synthesis technology.
  • the face area and the compressed non-specific area are combined into a complete image; in Fig. 6, the compression ratio of the face area and the non-specific area except the image is determined by a preset manner, and an image segmentation technique is added.
  • the face area of the image is separated from the non-specific area, wait until the map
  • the compressed face region and the compressed non-specific region are synthesized into a complete image by image synthesis technology. It can be seen that the same point in FIG. 2 and FIG.
  • FIG. 3 is that the image is not divided, so there is no need to synthesize after the image is compressed, and the difference is that the manner of determining the image compression ratio is different
  • FIG. 3 is a calculation mode
  • FIG. 5 is a Preset mode
  • the same point in Figure 4 and Figure 5 is to divide the image, so the image needs to be synthesized after the image is compressed.
  • the difference is that the image compression ratio is different.
  • Figure 4 is the calculation mode
  • Figure 6 is the calculation mode. Preset mode. Therefore, the image compression method disclosed in the embodiment of the present invention identifies a specific area and a non-specific area of an image by using a face recognition technology, and uses different compression ratios for a specific area and a specific area according to the network congestion degree.
  • the non-specific area is compressed, and the non-specific area is preferentially compressed. This ensures that the specific area that the user is most concerned with is not greatly compressed, and can also satisfy a certain transmission fluency.
  • the image compression device of the embodiment of the present invention includes: a detecting unit 71, a first calculating unit 72, a second calculating unit 73, an identifying unit 75, and a compressing unit. 76.
  • the detecting unit 71 is configured to detect a network congestion degree of the image transmission network; the first calculating unit 72 is configured to calculate an available transmission rate of the transmission network transmission image according to the network congestion degree; and the second calculating unit 73 is configured to use according to the available
  • the transmission rate calculates a data amount threshold of the transmission network transmission single frame image; the identification unit 75 is configured to identify a specific area in the image when the data amount of the transmitted image is greater than the data amount threshold of the single frame image And a non-specific area; the compression unit 76 is configured to compress a specific area and a non-specific area in the image according to different compression ratios.
  • the specific area may be a face area
  • the non-specific area is a deduction of a face area
  • the identification unit 75 is specifically configured to identify a face area of the image in the video stream as a specific area by using a face recognition technology, and the face area of the image is a non-specific area.
  • the image compression apparatus further includes a receiving unit, configured to receive an instruction that the user uses to specify the area; the specific area is a user-specified area, and the non-specific area is an area other than the area specified by the user. . In this way, the user can conveniently specify a certain area or certain areas, so that when the data transmission environment is poor, the definition of one or some areas is preferentially guaranteed while ensuring a certain degree of fluency.
  • the apparatus further includes a third calculating unit 74, configured to: according to the data amount of the specific area, the data amount of the non-specific area, and the data volume of the single-frame image transmitted by the network A threshold, a first compression ratio for the particular region and a second compression ratio for the non-specific region are calculated.
  • the specific implementation process is as follows: When the data amount of the face area of the image is smaller than the data amount threshold, the first compression ratio of the face area of the image is 100°/.
  • the first compression ratio of the non-specific area of the image is a ratio obtained by dividing the difference between the data amount threshold and the data amount of the face area by the data amount of the non-specific area
  • the second compression ratio of the non-specific region of the image is 0, and the first compression ratio of the face region is The ratio of the amount of data of the face region to the threshold of the data amount.
  • the method is more flexible, and the first compression ratio, the second compression ratio, may be calculated in real time according to the data amount of the specific area, the data volume of the non-specific area, and the data quantity threshold of the network transmission single frame image. This ensures that the specific area is clear when the network transmission speed is low, and the smoothness and real-time performance of the video communication can be ensured.
  • the device further includes an image dividing unit 81 and an image synthesizing unit 84.
  • the image dividing unit 81 is configured to divide the image into a specific area and a non-specific area, for example: when the specific area refers to a face area, the image dividing unit 81 divides the image into a person by image segmentation technology.
  • the method of dividing the image into the face area and the non-specific area may be other areas of the image except the recognized face area. It is a non-specific area; it can also be directly divided into a face area and a non-specific area by image segmentation technology.
  • the image synthesizing unit 84 is configured to perform a synthesizing process on the compressed unspecified area and the compressed face area.
  • the image compression device disclosed in the embodiment of the present invention detects the network congestion degree of the image transmission network by using the detection unit, and the first calculation unit calculates an available transmission rate of the transmission network transmission image according to the network congestion degree, and the second calculation unit is configured according to the Calculating a data volume threshold of the transmission network transmission single frame image, where the data amount of the transmitted image is greater than a data amount threshold of the single frame image, the identification unit identifies a specific region in the image and The non-specific area, the compression unit compresses the specific area and the non-specific area in the image according to different compression ratios, preferentially compresses the non-specific area, thereby ensuring that the specific area most concerned by the user is not greatly compressed, and Can meet certain transmission fluency.
  • the device is suitable for ensuring clearness of a specific area when the network transmission speed is low, and ensuring the smoothness and real-time performance
  • the mobile terminal disclosed in the embodiment of the present invention includes the image compression device in the seventh embodiment, and the mobile terminal sends the compressed image to the mobile terminal at the opposite end, which can ensure that the network transmission speed is low and is used.
  • a mobile terminal performs video data exchange, it ensures that a specific area that the user pays most attention to is clear, and can also satisfy a certain transmission smoothness.
  • the elements and algorithm steps of the various examples described in connection with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both, in order to clearly illustrate hardware and software. Interchangeability, the composition and steps of the various examples have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the solution. A skilled person can use different methods for implementing the described functions for each particular application, but such implementation should not be considered to be beyond the scope of the present invention.
  • the steps of a method or algorithm described in connection with the embodiments disclosed herein can be implemented in hardware, a software module executed by a processor, or a combination of both.
  • the software module can be placed in random access memory (RAM), memory, read only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or technical field. Any known It is in the form of a storage shield.

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Abstract

本发明实施例涉及一种图像压缩方法和装置，该方法具体包括：检测图像传输网络的网络拥塞度，根据所述网络拥塞度计算所述传输网络传输图像的可用传输速率，根据所述可用传输速率计算所述传输网络传输单帧图像的数据量阈值，当传输的所述图像的数据量大于所述单帧图像的数据量阈值时，识别所述图像中的特定区域和非特定区域，将所述图像中的特定区域和非特定区域按照不同压缩比进行压缩后传输，因此，本发明实施例公开的方法和装置，在数据传输环境较差时，实现了对所述图像的特定区域和非特定区域进行区分处理，提高了用户接收到图像的特定区域的清晰度同时又能保证一定的流畅度。

Description

图像压缩方法和装置 本申请要求于 2012年 04月 17日提交中国专利局、 申请号为 201210112729.9、 发明名称为 "图像压缩方法和装置" 的中国专利申请的优 先权， 其全部内容通过引用结合在本申请中。 技术领域
本发明涉及图像处理领域， 尤其涉及一种图像压缩方法和装置。 背景技术
随着通信技术的发展和网络带宽的快速提升， 视频通话技术越来越成 熟， 同时视频通话的应用也会越来越普及。 尤其是作为第三代移动通信技 术（ 3rd-generation, 3G )手机的核心应用， 正在受到各方的广泛关注， 同 时加速了视频通话技术的更快发展。
在视频通话过程中， 视频通话的通话流畅度和视频画面的清晰度是衡 量视频通话质量的两个关键指标。 尤其当通信负载很大时， 既要保证视频 通话的通话流畅度又要做到图像比较清晰是非常困难的事情。
在现有技术中， 当遇到通信负载很大或者信号强度很弱时， 为了保证 视频通话的速度， 往往牺牲视频画面的质量。 对图像的一般处理方法是大 幅度减小图像的分辨率。 具体实现为， 首先通过分析视频通话中数据链路 层的通信量或者信号的强度， 然后根据通信量的大小以及视频信号的受干 扰程度对图像进行缩小分辨率处理， 以减小用于网络传输的单帧图像的数 据量， 保证视频信号实时传输的流畅性。
但是， 由于图像的分辨率的大幅度减少， 图像的质量将会更大程度的 下降， 这样直接严重影响了图像的清晰度， 故存在图像的清晰度低的问题。 发明内容 本发明实施例提供了一种图像压缩方法和装置， 以实现在视频通话过 程中， 数据传输环境较差时尽可能保证特定区域的清晰度的同时又能保证 一定的流畅度。
在第一方面， 本发明提供了一种图像压缩方法， 所述方法包括： 检测图像传输网络的网络拥塞度；
根据所述网络拥塞度计算所述传输网络传输图像的可用传输速率； 根据所述可用传输速率计算所述传输网络传输单帧图像的数据量阈 值；
当传输的所述图像的数据量大于所述单帧图像的数据量阈值时， 识别 所述图像中的特定区域和非特定区域；
将所述图像中的特定区域和非特定区域按照不同压缩比进行压缩。 在第二方面， 本发明提供了一种图像压缩装置， 所述装置包括： 检测单元， 用于检测图像传输网络的网络拥塞度；
第一计算单元， 用于根据所述网络拥塞度计算所述传输网络传输图像 的可用传输速率；
第二计算单元， 用于根据所述可用传输速率计算所述传输网络传输单 帧图像的数据量阈值；
识别单元， 用于当传输的所述图像的数据量大于所述单帧图像的数据 量阈值时， 识别所述图像中的特定区域和非特定区域；
压缩单元， 用于将所述图像中的特定区域和非特定区域按照不同压缩 比进行压缩。
本发明实施例提供的图像压缩方法和装置， 通过检测图像传输网络的 网
络拥塞度； 根据所述网络拥塞度计算所述传输网络传输图像的可用传 输速率； 根据所述可用传输速率计算所述传输网络传输单帧图像的数据量 阈值； 当传输的所述图像的数据量大于所述单帧图像的数据量阈值时， 识 别所述图像中的特定区域和非特定区域； 将所述图像中的特定区域和非特 定区域按照不同压缩比进行压缩， 从而在数据传输环境较差时， 实现了对 所述图像的特定区域和非特定区域进行区分处理， 从而提高了用户接收到 图像的特定区域的清晰度， 同时又能保证一定的流畅度。 附图说明
图 1为本发明实施例一图像压缩方法的示意图；
图 2为本发明实施例二图像压缩方法的流程图；
图 3为本发明实施例三图像压缩方法的流程图；
图 4为本发明实施例四图像压缩方法的流程图；
图 5为本发明实施例五图像压缩方法的流程图；
图 6为本发明实施例六图像压缩方法的流程图；
图 7为本发明实施例七图像压缩装置的示意图；
图 8为本发明实施例八图像压缩装置的示意图。 具体实 itt式
为使本发明实施例的目的、 技术方案和优点更加清楚， 下面将结合本 发明实施例中的附图， 对本发明实施例中的技术方案进行清楚、 完整地描 述， 显然， 所描述的实施例是本发明一部分实施例， 而不是全部的实施例。 基于本发明中的实施例， 本领域普通技术人员在没有作出创造性劳动前提 下所获得的所有其他实施例， 都属于本发明保护的范围。
图 1 为本发明的实施例一图像压缩方法的示意图， 其中， 特定区域以 人脸区域为例进行说明。 如图所示， 本实施例包括原始图像 11、 识别出人 脸区域的图像 12、 人脸区域 1 3、 非特定区域 14、 压缩后的人脸区域 15、 压缩后的非特定区域 16和完整的压缩后的图像 17。
根据检测到图像传输网络的网络拥塞度确定若想保证传输图像的实时 性、 和流畅性就必须对原始图像进行压缩。 在本实施例中， 不是对原始图 像整体压缩， 而是对图像的内部内容进行区分处理。 因为原始图像中既包 括用户指定的区域即特定区域也包括扣除人脸区域以外的区域即非特定区 域， 比如原始图像 11中的人脸区域是特定区域， 而原始图像中扣除了人脸 区域后， 剩余的其他区域是非特定区域。 通过人脸识别技术识别原始图像 11 中的人脸区域， 即识别出人脸区域的图像 12 , 识别出人脸区域 1 3后， 图像的其他区域为非特定区域 14 ,按照不同压缩比对人脸区域 1 3和非特定 区域 14进行压缩， 得到压缩后的人脸区域 15和压缩后的非特定区域 16 , 压缩后的人脸区域 15和压缩后的非特定区域 16组成完整的压缩后的图像 17。
另夕卜，也可以首先通过图像分割技术将识别出特定区域的图像 12分割 为人脸区域 1 3和非特定区域 14 ,然后通过图像压缩技术按照不同压缩比对 人脸区域 1 3和非特定区域 14进行压缩， 得到压缩后的人脸区域 15和压缩 后的非特定区域 16 ,再次通过图像合成技术将压缩后的人脸区域 15和压缩 后的非特定区域 16合成成为完整的压缩后的图像 17。
图 2为本发明实施例二图像压缩方法的流程图。 如图所示， 本实施例 具体包括以下步骤：
步骤 21 0 ,通过反馈机制来检测图像传输网络的网络拥塞度，具体的参 数有丢包率、 平均队列长度、 超时重传的包的数目和平均包延迟等。
步骤 220 ,根据网络拥塞度计算传输网络传输图像的可用传输速率。一 般来讲， 网络拥塞度越高， 可用传输速率越小； 反之， 网络拥塞度越低， 可用传输速率越大。
步骤 230 , 根据可用传输速率计算传输网络传输单帧图像的数据量阈 值， 也就是根据可用传输速率计算单帧图像的大小限制。 只有需要传输的 每帧图像小于或等于单帧图像的大小限制时， 才能保证图像实时传输的流 畅性。
步骤 240 , 判断传输图像的数据量是否大于单帧图像的数据量阈值。 具体地， 若想保证图像实时传输的流畅性， 就必须将图像的每一帧图 像与根据网络拥塞度计算出的单帧图像的数据量阈值做比较。 若图像的每 一帧图像小于或等于单帧图像的数据量阈值， 则说明此时的网络拥塞度很 低， 属于正常值， 不需要对图像进行压缩就能保证视频通话的清晰度和实 时性， 则进行步骤 250直接传输原始的图像； 若图像的每一帧图像大于单 帧图像的数据量阈值， 则说明此时的网络拥塞度较高， 属于非正常值， 需 要对图像进行压缩才能保证视频通话实时性， 对于视频通话的清晰度， 优 先保证图像部分区域的清晰度， 则进行到步骤 260。
步骤 250 , 当确定图像的每一帧图像小于或等于单帧图像的数据量阈 值， 则说明此时的网络拥塞度很低， 属于正常值， 不需要对图像进行压缩 就能保证视频通话的清晰度和实时性， 则直接传输原始的图像。
步骤 260,当传输的所述图像的数据量大于所述单帧图像的数据量阈值 时， 接收用户指定区域的指令并确定图像的特定区域。
其中， 图像的特定区域可以是人脸区域， 也可以是用户指定的任何区 域， 图像的非特定区域是扣除用户指定的区域以外的区域。
具体地， 用户可以指定图像中任何区域为特定区域。 另外， 用户也可 以指定多个特定区域。 比如， 图像中多个需要保持清晰度的具体实物， 用 户可以指定这多个具体事物为特定区域。 而图像中扣除特定区域后其他的 区域为非特定区域。 这样一来， 可以使得用户很方便的指定某个或者某些 区域， 使得在数据传输环境较差时， 优先保证某个或者某些区域的清晰度 同时又能保证一定的流畅度。
步骤 270, 通过人脸识别技术识别图像中的特定区域和非特定区域。 具体地， 通过人脸识别技术识别出视频流中的图像的人脸区域， 再将 图像划分为人脸区域和非特定区域。 将图像划分为人脸区域和非特定区域 的技术可以通过人脸识别技术识别出图像的人脸区域， 图像的其他区域为 非特定区域， 或者识别出图像的人脸区域后再通过图像分割技术将图像分 割为人脸区域和非特定区域。
步骤 280,将所述图像中的特定区域和非特定区域按照不同压缩比进行 压缩。
具体地， 特定区域可以为人脸区域， 非特定区域为扣除人脸区域以外 的区域。 根据单帧图像的数据量阈值， 分别计算图像的人脸区域和非特定 区 i或的压缩比。
当图像的人脸区域的数据量 AD小于所述数据量阈值 D时， 则图像的人 脸区域的第一压缩比 r l为 100%, 而图像的非特定区域的第二压缩比 r2为 数据量阈值 D和人脸区域的数据量 AD相减后的差值再除以非特定区域的数 据量 BD后得到的比值， 具体如下：
rl=100% 公式（ 1 ) r2= ( D-AD ) /BD 公式（2 ) 当图像的人脸区域的数据量 AD不小于所述数据量阈值 D时， 则所述图 像的非特定区域的第二压缩比 r2为 0,而所述人脸区域的第一压缩比 rl为 所述人脸区域的数据量 AD与所述数据量阈值 D的比值；
rl=AD/D 公式（ 3 ) r2=0 公式（ 4 ) 上述对图像的人脸区域和非特定区域采用不同压缩比进行压缩。 为了 保证用户最关心地人脸部分的清晰度， 优先对图像的非特定区域进行压缩。 当网络拥塞度较高， 属于非正常值时， 对图像的非特定区域进行压缩， 而 不对图像的人脸区域进行压缩， 这时压缩后的图像是人脸区域较为清晰而 背景相对模糊的图像； 当网络拥塞度非常高时， 对图像的非特定区域进行 压缩到了极限， 还不能保证图像传输的一定流畅度， 则对图像的人脸区域 也进行压缩， 这时压缩后的图像是人脸区域相对清晰而背景非常模糊的图 像。
下面结合图 3、 图 4、 图 5和图 6对图 2中步骤 270具体的工作过程做 详细描述。
图 3 为本发明实施例三图像压缩方法的流程图。 如图所示， 本实施例 将图像中的特定区域和非特定区域按照不同压缩比进行压缩的过程具体包 括以下步骤： 步骤 301 , 图像的特定区域为人脸区域，非特定区域为扣除人脸区域以 外的区域。 获取人脸区域的数据量和非特定区域的数据量。 该图像数据包 括人脸区域数据和非特定区域的数据。
步骤 302 ,比较人脸区域数据量是否小于网络传输单帧图像的数据量阈 值， 当人脸区域数据量小于网络传输单帧图像的数据量阈值时， 说明只对 非特定区域压缩后就能够保证图像实时传输的流畅性， 这样就保证了人脸 区域的清晰度， 则进行步骤 303; 当人脸区域数据量小于网络传输单帧图像 的数据量时， 说明仅仅对非特定区域压缩后还不能保证图像实时传输的流 畅性， 则进行步骤 305。
步骤 303 , 当人脸区域数据量小于网络传输单帧图像的数据量阈值时， 计算人脸区域的第一压缩比 r l和非特定区域的第二压缩比 r2 ,具体计算方 法如公式（ 1 )和公式（ 1 )。
步骤 304 , 利用利用计算出的人脸区域的第一压缩比 r l和非特定区域 的第二压缩比 Rr 2 分别对人脸区域和非特定区域进行压缩。 即优先对图像 的非特定区域进行压缩， 而不对图像的人脸区域进行压缩。 人脸区域的第 一压缩比 r l大于非特定区域的第二压缩比 r2。
具体地， 根据网络拥塞度， 同时为了保证用户最关心地人脸部分的清 晰度， 优先对图像的非特定区域进行压缩， 这时压缩后的图像是人脸区域 较为清晰而背景相对模糊的图像。
步骤 305 , 当人脸区域数据量不小于网络传输单帧图像的数据量阈值 时， 计算人脸区域的第一压缩比 r l和非特定区域的第二压缩比 r2 , 具体计 算方法如公式（3 )和公式（4 )。
步骤 306 ,利用计算出的人脸区域的第一压缩比 r l和非特定区域的第 二压缩比 r2分别对人脸区域和非特定区域进行压缩。 即不再传输非特定区 域的数据， 只传输压缩后的人脸图像。人脸区域的第一压缩比 r l大于非特 定区域的第二压缩比 r 2。 此时压缩后的图像是人脸区域相对清晰的图像。 另外， 计算压缩比的方法很多， 除了利用公式（1 )、 （2 )、 （3 )和（4 ) 计算压缩比， 还包括其他的计算压缩比的方法， 在这里不再——列举。
上述压缩方式根据获取人脸区域的数据量、 非特定区域的数据量和网 络传输单帧图像的数据量阈值计算人脸区域和非特定区域的压缩比， 再利 用计算出的对人脸区域和非特定区域进行压缩， 当网络传输单帧图像的数 据量阈值变化时， 人脸区域和非特定区域的压缩比也在变化， 保证了用户 接收到图像的特定区域的清晰度的同时又能保证一定的流畅度。
图 4 为本发明实施例四图像压缩方法的流程图。 如图所示， 本实施例 完成将图像中的特定区域和非特定区域按照不同压缩比进行压缩的过程具 体包括以下步骤：
步骤 401 , 图像的特定区域为人脸区域， 非特定区域为扣除人脸区域以 外的区域。 对图像的非特定区域预设第一压缩比， 对图像的人脸区域预设 第二压缩比。
步骤 402 , 利用预设的第一压缩比对图像的非特定区域进行压缩， 利用 预设的第二压缩比对图像的人脸区域进行压缩。
图 5 为本发明实施例五图像压缩方法的流程图。 如图所示， 本实施例 完成将图像中的特定区域和非特定区域按照不同压缩比进行压缩后传输的 过程具体包括以下步骤：
步骤 501 , 图像的特定区域为人脸区域，非特定区域为扣除人脸区域以 外的区域。 利用图像分割技术将图像分割为人脸区域和非特定区域。
步骤 502至步骤 507 ,与图 3中步骤 301至步骤 306内容相同，在这里 不再详细说明。
步骤 508 ,利用图像合成技术将压缩后的人脸区域和压缩后的非特定区 域进行合成。
上述压缩方式通过图像分割技术将所述图像分割为人脸区域和非特定 区域并通过图像合成技术将压缩后的人脸区域和压缩后的非特定区域进行 合成， 这样可以更好的对所述图像的特定区域和非特定区域进行压缩。 图 6 为本发明实施例六图像压缩方法的流程图。 如图所示， 本实施例 完成将图像中的特定区域和非特定区域按照不同压缩比进行压缩后传输的 过程具体包括以下步骤：
步骤 601 , 图像的特定区域为人脸区域， 非特定区域为扣除人脸区域以 外的区域。 利用图像分割技术将图像分割为人脸区域和非特定区域。
步骤 603 , 利用预设的第一压缩比对图像的人脸区域进行压缩， 利用预 设的第二压缩比对图像的非特定进行压缩。
步骤 604 ,利用图像合成技术将压缩后的人脸区域和压缩后的非特定区 域合成完整的图像。
上述描述中， 结合图 3、 图 4、 图 5和图 6详细说明了图 2中步骤 270 中将图像中的特定区域和非特定区域按照不同压缩比进行压缩后传输的具 体实现过程。 在图 3、 图 4、 图 5和图 6中， 特定区域为人脸区域， 非特定 区域为扣除人脸区域以外的区域。
图 3、 图 4、 图 5和图 6共描述了四种不同的工作过程， 这四种工作过 程有相同点也有不同点。 图 3 中图像的人脸区域和非特定区域的压缩比是 根据网络拥塞度并通过计算的方式确定的， 优先压缩非特定区域， 在非特 定区域压缩极限的情况下再对人脸区域进行压缩； 图 4 中图像的人脸区域 和非特定区域的压缩比是通过预设的方式确定的； 图 5 中除了图像的人脸 区域和非特定区域的压缩比是根据网络拥塞度并通过计算的方式确定的， 压缩之外， 还增添了通过图像分割技术将图像的人脸区域和非特定区域分 割开， 等到将图像的人脸区域和非特定区域压缩后， 通过图像合成技术将 压缩后的人脸区域和压缩后的非特定区域合成为完整图像； 图 6 中除了图 像的人脸区域和非特定区域的压缩比是通过预设的方式确定的之外， 还增 添了通过图像分割技术将图像的人脸区域和非特定区域分割开， 等到将图 像的人脸区域和非特定区域压缩后， 通过图像合成技术将压缩后的人脸区 域和压缩后的非特定区域合成为完整图像。 由此可见， 图 2和图 3的相同 点是没有将图像进行分割， 所以对图像压缩后也不需要合成， 其不同点是 确定图像压缩比的方式不同， 图 3是计算方式而图 5是预设方式； 图 4和 图 5 的相同点是将图像进行分割， 所以对图像压缩后还需要将图像合成， 其不同点是确定图像压缩比的方式不同， 图 4是计算方式而图 6是预设方 式。 因此， 本发明实施例公开的图像压缩方法， 通过人脸识别技术识别出 图像的特定区域和非特定区域， 并且根据网络拥塞度对特定区域和非特定 区域采用不同的压缩比分别对特定区域和非特定区域进行压缩， 优先压缩 非特定区域， 这样可以保证用户最关注的特定区域不会被大幅度的压缩， 而且还能满足一定的传输流畅度。
图 Ί 为本发明实施例七图像压缩装置的示意图， 如图所示， 本实施例 图像压缩装置具体包括：检测单元 71、第一计算单元 72、第二计算单元 73、 识别单元 75、 压缩单元 76。
检测单元 71 用于检测图像传输网络的网络拥塞度； 第一计算单元 72 用于根据所述网络拥塞度计算所述传输网络传输图像的可用传输速率； 第 二计算单元 73用于根据所述可用传输速率计算所述传输网络传输单帧图像 的数据量阈值； 识别单元 75用于当传输的所述图像的数据量大于所述单帧 图像的数据量阈值时， 识别所述图像中的特定区域和非特定区域； 压缩单 元 76 用于将所述图像中的特定区域和非特定区域按照不同压缩比进行压 缩。
其中， 当所述特定区域可以为人脸区域， 所述非特定区域是扣除人脸 区
域以外的区域时； 所述识别单元 75 , 具体用于利用人脸识别技术， 识别视 频流中的图像的人脸区域为特定区域， 所述图像中扣除人脸区域为非特定 区域。 进一步的， 所述图像压缩装置还包括接收单元， 用于接收用户用于指 定区域的指令； 所述特定区域是用户指定的区域， 所述非特定区域是扣除 所述用户指定的区域以外的区域。 这样一来， 可以使得用户很方便的指定 某个或者某些区域， 使得在数据传输环境较差时， 优先保证某个或者某些 区域的清晰度同时又能保证一定的流畅度。
进一步的， 如图 8所示， 所述装置还包括第三计算单元 74 , 用于根据 所述特定区域的数据量、 所述非特定区域的数据量和所述网络传输单帧图 像的数据量阈值， 计算出针对所述特定区域的第一压缩比和针对所述非特 定区域的第二压缩比。 具体的实现过程如下： 当所述图像的人脸区域的数 据量小于所述数据量阈值时，则所述图像的人脸区域的第一压缩比为 100°/。， 而所述图像的非特定区域的第一压缩比为所述数据量阈值和所述人脸区域 的数据量相减后的差值再除以所述非特定区域的数据量后得到的比值； 当 所述图像的人脸区域的数据量不小于所述数据量阈值时， 则所述图像的非 特定区域的第二压缩比为 0,而所述人脸区域的第一压缩比为所述人脸区域 的数据量与所述数据量阈值的比值。 这种方式更加灵活， 可以根据所述特 定区域的数据量、 所述非特定区域的数据量和所述网络传输单帧图像的数 据量阈值实时的计算出第一压缩比， 第二压缩比， 使得在网络传输速度较 低较差时保证特定区域较为清晰， 又能保证视频通信的流畅性和实时性。
更进一步的， 所述装置还包括图像分割单元 81、 图像合成单元 84。 所 述图像分割单元 81 , 用于将所述图像分割为特定区域和非特定区域， 例如： 当特定区域指的是人脸区域时， 图像分割单元 81中通过图像分割技术将所 述图像分割为人脸区域和非特定区域， 识别出视频通话的视频流中的图像 的人脸区域之后， 将图像划分为人脸区域和非特定区域的方法可以为除了 识别出的人脸区域外， 图像的其他区域为非特定区域； 还可以通过图像分 割技术将图像直接分割为人脸区域和非特定区域。 所述图像合成单元 84用 于将所述压缩后的非特定区域和压缩后的人脸区域进行合成处理。 本发明实施例公开的图像压缩装置， 通过检测单元检测图像传输网络 的网络拥塞度， 第一计算单元根据所述网络拥塞度计算所述传输网络传输 图像的可用传输速率， 第二计算单元根据所述可用传输速率计算所述传输 网络传输单帧图像的数据量阈值， 当传输的所述图像的数据量大于所述单 帧图像的数据量阈值时， 识别单元识别所述图像中的特定区域和非特定区 域， 压缩单元将所述图像中的特定区域和非特定区域按照不同压缩比进行 压缩， 优先压缩非特定区域， 从而可以保证用户最关注的特定区域不会被 大幅度的压缩， 而且还能满足一定的传输流畅度。 该装置适用于网络传输 速度较低较差时保证特定区域较为清晰， 又能保证视频通信的流畅性和实 时性。
本发明实施例公开的一种移动终端， 包含上述实施例 7 中的图像压缩 装置， 该移动终端会将压缩后的图像发送给对端的移动终端， 可以保证在 网络传输速度较低较差， 使用此种移动终端进行视频数据交换时， 保证用 户最关注的特定区域较为清晰， 而且还能满足一定的传输流畅度。 专业人员应该还可以进一步意识到， 结合本文中所公开的实施例描述 的各示例的单元及算法步骤， 能够以电子硬件、 计算机软件或者二者的结 合来实现， 为了清楚地说明硬件和软件的可互换性， 在上述说明中已经按 照功能一般性地描述了各示例的组成及步骤。 这些功能究竟以硬件还是软 件方式来执行， 取决于技术方案的特定应用和设计约束条件。 专业技术人 员可以对每个特定的应用来使用不同方法来实现所描述的功能， 但是这种 实现不应认为超出本发明的范围。
结合本文中所公开的实施例描述的方法或算法的步骤可以用硬件、 处 理器执行的软件模块， 或者二者的结合来实施。 软件模块可以置于随机存 储器（RAM )、 内存、 只读存储器（R0M )、 电可编程 R0M、 电可擦除可编程 ROM, 寄存器、 硬盘、 可移动磁盘、 CD-ROM, 或技术领域内所公知的任意其 它形式的存储介盾中。
以上所述的具体实施方式， 对本发明的目的、 技术方案和有益效果进 行了进一步详细说明， 所应理解的是， 以上所述仅为本发明的具体实施方 式而已， 并不用于限定本发明的保护范围， 凡在本发明的精神和原则之内， 所做的任何修改、 等同替换、 改进等， 均应包含在本发明的保护范围之内。

Claims

权利要求
1、 一种图像压缩方法， 其特征在于， 所述方法包括：
检测图像传输网络的网络拥塞度；
根据所述网络拥塞度计算所述传输网络传输图像的可用传输速率； 根据所述可用传输速率计算所述传输网络传输单帧图像的数据量阈 值；
当传输的所述图像的数据量大于所述单帧图像的数据量阈值时， 识别 所述图像中的特定区域和非特定区域；
将所述图像中的特定区域和非特定区域按照不同压缩比进行压缩。
2、 根据权利要求 1所述的图像压缩方法，其特征在于，所述特定区域 为人脸区域， 所述非特定区域为扣除人脸区域以外的区域；
所述识别所述图像中的特定区域和非特定区域具体为： 利用人脸识别 技术， 识别视频通话的视频流中的图像的人脸区域为特定区域， 所述图像 中扣除人脸区域为非特定区域。
3、 根据权利要求 2所述的图像压缩方法，其特征在于，所述识别所述 图像中的特定区域和非特定区域之前， 包括：
接收用户用于指定区域的指令；
所述特定区域是用户指定的区域， 所述非特定区域是扣除所述用户指 定的区域以外的区域。
4、 根据权利要求 3所述的图像压缩方法，其特征在于，所述将所述图 像中的特定区域和非特定区域按照不同压缩比进行压缩之前还包括：
根据所述特定区域的数据量、 所述非特定区域的数据量和所述网络传 输单帧图像的数据量阈值， 计算出针对所述特定区域的第一压缩比和针对 所述非特定区域的第二压缩比。
5、 根据权利要求 3所述的图像压缩方法，其特征在于，所述将所述图 像中的特定区域和非特定区域按照不同压缩比进行压缩具体包括： 对所述非特定区域利用预设的第一压缩比进行压缩处理， 对所述人脸 区域利用预设的第二压缩比进行压缩处理。
6、 根据权利要求 4或 5所述的图像压缩方法，其特征在于，所述识别 所述图像中的特定区域和非特定区域之后还包括： 将所述图像分割为特定 区域和非特定区域；
将所述图像中的特定区域和非特定区域按照不同压缩比进行压缩之后 还包括， 将所述压缩后的特定区域和压缩后的非特定区域进行合成处理。
7、 一种图像压缩装置， 其特征在于， 所述装置包括：
检测单元， 用于检测图像传输网络的网络拥塞度；
第一计算单元， 用于根据所述网络拥塞度计算所述传输网络传输图像 的可用传输速率；
第二计算单元， 用于根据所述可用传输速率计算所述传输网络传输单 帧图像的数据量阈值；
识别单元， 用于当传输的所述图像的数据量大于所述单帧图像的数据 量阈值时， 识别所述图像中的特定区域和非特定区域；
压缩单元， 用于将所述图像中的特定区域和非特定区域按照不同压缩 比进行压缩。
8、 根据权利要求 7所述的图像压缩装置，其特征在于， 当所述特定区 域为人脸区域， 所述非特定区域是扣除人脸区域以外的区域时；
所述识别单元， 具体用于利用人脸识别技术， 识别视频流中的图像的 人脸区域为特定区域， 所述图像中扣除人脸区域为非特定区域。
9、 根据权利要求 8所述的图像压缩装置， 其特征在于， 所述装置还包 括：
接收单元， 用于接收用户指定区域的指令； 所述特定区域是用户指定 的区域， 所述非特定区域是扣除所述用户指定的区域以外的区域。
10、 根据权利要求 9 所述的图像压缩装置， 其特征在于， 所述装置还 包括：
第三计算单元， 用于根据所述特定区域的数据量、 所述非特定区域的 数据量和所述网络传输单帧图像的数据量阈值， 计算出针对所述特定区域 的第一压缩比和针对所述非特定区域的第二压缩比。
11、 根据权利要求 9 所述的图像压缩装置， 其特征在于， 所述压缩单 元， 具体用于对所述非特定区域利用预设的第一压缩比进行压缩处理， 对 所述人脸区域利用预设的第二压缩比进行压缩处理。
12、 根据权利要求 10或 11所述的图像压缩装置， 其特征在于， 所述 装置还包括：
图像分割单元， 用于将所述图像分割为特定区域和非特定区域； 图像合成单元， 用于将所述压缩后的特定区域和压缩后的非特定区域 进行合成处理。
13、 一种移动终端， 其特征在于， 包含如权利要求 7至权利要求 12中任 一项所述的图像压缩装置。
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