Abstract:
A method for determining spatial and temporal loss in a packet based video broadcast system in an encrypted environment involves measuring video coding layer information at an unencrypted head end of a video stream and network layer information at an encrypted downstream end of the same video stream. Video coding layer information is correlated with network layer information having a corresponding time stamp to compute the spatial and temporal loss. The video coding layer and network layer information is taken from discrete segments of the video stream including access units, slices or macroblocks. Impairments in the video stream are determined using the computed spatial and temporal loss.

Description:
BACKGROUND OF THE INVENTION 
   The present invention relates generally to packet based video broadcast systems. More particularly, the present invention pertains to methods of estimating the extent of loss of video coding layer information and their impact in a series of images in an encrypted video stream that uses MPEG2/4/H.264-AVC compatible encoding. 
   In typical broadcast systems, such as in IPTV (Internet Protocol Television) and direct broadcast satellite (DBS) applications, multiple video programs are encoded in parallel, and the digitally compressed bitstreams are multiplexed onto a single, constant or variable bit rate channel. The video coding layer (MPEG2/H.264-AVC) is typically packetized into small fixed-size packets (MPEG2 Transport Stream) before transmission to an IP network. Typical packet losses in an IP network could follow various loss distributions where each loss event could be single, consecutive or sparse burst losses. This loss will result in a discard of a frame, slice or macroblock/s at the video coding layer. These macroblocks could either be INTER or INTRA predicted and could be part of the reference frame list, in which case the temporal duration of the loss could extend for a few frames in sequence. 
   Just measuring the packet loss rate at the IP level is insufficient to determine the loss propagation at the video content layer. The visual impact of IP packet loss must be determined by analyzing the loss propagation at the video content layer. In addition, coding quality is largely dependent on the quantization errors, the distribution of quantization at each macroblock determines the coding quality, the higher the quantization, the higher the loss of DCT coefficients, that results in low image quality. In an encrypted environment all the information that is needed to determine the spatial and temporal extent of the propagation of errors and quantization data is unavailable. Typically, the transport stream payload is encrypted. This payload contains the information about the video coding layer information at various sections, frames, slices and macroblocks. What is needed is a method to determine this information when the video stream monitored by the measurement device is encrypted. 
   MPEG encoded variable bit rate (VBR) video traffic is expected to dominate the bandwidth of broadband networks. Such traffic can be delivered in streaming, on demand, IPTV or DBS types of environments. Accurate models must take into account both capped VBR or CBR types of environment, video complexity and spatial/temporal propagation of errors under various loss distribution patterns. These parameters are necessary to enable monitoring systems for prediction of performance of any proposed network during its operation.  FIG. 1  shows components that are involved in delivering video content in a typical IPTV environment. Video source that originates as analog signal is encoded using an encoder and packetized and sent using an IP network. It could be sent as multicast or unicast destination to the network. The core contains various elements to provision and manage subscribers and traffic flows. The content is stored in content servers and delivered to the user on demand. 
   MPEG coding standards define timing information at various sections in a video that is used by the Video decoding process.  FIG. 2  shows the packet layers where this timing information is present. There is a single, common system clock in the encoder. This clock is used to create timestamps that indicate the correct presentation and decoding timing of audio and video, as well as to create timestamps that indicate the instantaneous values of the system clock itself at sample intervals. The timestamps that indicate the presentation time of video and audio are called Presentation Timestamps (PTS). Timestamps that indicate the decoding time are called Decoding Timestamps (DTS). Those timestamps that indicate the value of the system clock are called Program Clock Reference (PCR) in transport streams. 
   Accordingly, what is needed is a process to analyze video timing information at the head end and down stream (IPTV content distribution site as in  FIG. 1 ), and correlate information from the head end to the down stream video sample instance. The present invention fulfills these needs and provides other related advantages. 
   SUMMARY OF THE INVENTION 
   The present invention provides a method for estimating loss of Video Coding Layer information in real time. This is accomplished by the analysis of video timing from the unencrypted head end and encrypted down stream of the video stream, and correlating the information at a collection location. Once this information is determined, the effects of a loss/loss distribution event of an IP packet is are computed by determining the spatial and temporal extent of the video content loss. Quantization data and its distribution can also be determined by this method. 
   A process for determining spatial and temporal loss in a packet based video broadcast system in an encrypted environment involves collecting video coding layer information with a corresponding time stamp at an unencrypted head end of a video stream and simultaneously collecting network layer information with a corresponding time stamp at an encrypted downstream end of the video stream. The video coding layer information is correlated with the network layer information using the respective time stamps. Spatial and temporal loss in the video stream from the head end to the downstream end is computed using the correlated information. 
   The process includes the step of gathering information and parameters corresponding to discreet sections of the video stream during each of the collecting steps. The discreet sections of the video stream include access units, slices or macroblocks. The parameters in each access unit include correlation time, picture resolution, sequence number or instantaneous decoder refresh number. The parameters in each slice include slice identification, slice type or sequence number. The parameters in each macroblock include macroblock type, macroblock size, sequence number, reference index or loss flag. 
   The step of simultaneously collecting network layer information further includes the step of creating a statistical model representing packet loss distribution information for a loss event in the video stream. 
   The computing step also includes computing spatial and temporal loss duration, and slices or macroblocks affected by the loss event. The computing step further comprises the step of computing impairments in the video stream using the computed spatial and temporal loss. The computing step also includes mapping the video coding layer information and the network layer information to match IP/port data from the downstream end to the head end of the video stream, maintaining an access unit list and an associated reference picture list at an unencrypted status event, locating a match between the list of access units and an encrypted status event, and identifying lost packets in discreet sections of the access unit list and the associated reference picture list. 
   Other features and advantages of the present invention will become apparent from the following more detailed description, taken in connection with the accompanying drawings which illustrate, by way of example, the principals of the present invention. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
     The accompanying drawings illustrate the invention. In such drawings: 
       FIG. 1  shows an example of an IPTV (IP television) distribution network with potential points where measurements; 
       FIG. 2  shows a typical protocol stack where Video Coding Layer content is encapsulated in IP/UDP/MPEG2TS and values for both Network and Video Coding Layer statistics are extracted; 
       FIG. 3  shows a typical protocol stack where Video Coding Layer content is encapsulated in IP/UDP/RTP and values for both Network and Video Coding Layer statistics are extracted; 
       FIG. 4  shows the timing information options that are available to provide the correlation time; 
       FIG. 5  shows the parameters gathered at the Head End location for Video Coding Layer information; 
       FIG. 6  show the parameters gathered at the down stream location for Network Layer information; and 
       FIG. 7  shows the correlation module inputs at the collector that provides a correlated information output utilizing VCL and Network parameters. 
   

   DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT 
   The present invention relates to a method of estimating video coding layer information in a series of images in a video stream supporting MPEG2/4/H.264-AVC type of picture encoding, includes creating, during a flow of encoded video stream, statistics on video coding layer information at the head end, storing the prediction and motion information of macroblocks that pertains to a access unit/slice and available timing information (PCR) and transmitting the factors and timing to the collector. At the same time at the down stream end creating, during a flow of encoded video stream a statistical model representing the packet loss distribution information, storing the loss factors and timing information that is available—RTP/PCR/PTS, DTS or Statistics generation time and transmitting the factors and timing to the collector. The collector then correlates the Video Coding Layer sections information with the Network Layer information utilizing this timing information originating from head end and down stream locations. 
   As described below, the inventive method can provide image complexity measurements for industry wide video quality assessment models. One such model is described in U.S. patent application Ser. No. 11/456,505 filed on Jul. 10, 2006 entitled Image Complexity Computation in Packet-Based Video Broadcast Systems, the contents of which are incorporated by reference. 
   The present method provides a distributed system to estimate perceived video quality in an encrypted environment. The method allows collectors to get Video Coding Layer parameters and compute image complexity values from distributed remote probes analyzing video in an encrypted environment. The method facilitates computation of impairments in a packetized video stream using spatial and temporal statistics from the video content to more accurately measure perceived video quality. The method also provides image complexity at regular intervals for packetized video applications and an estimation on video complexity as perceived by a human visual system. Further, the method provides image complexity measurements for typical industry wide video quality assessment models, including and not limited to Peak Signal to Noise Ratio (PSNR), MPQM, MQUANT and Root Mean Square Error (RMSE), as well as offline and real time image complexity measurements that can be used or incorporated by video encoders, multiplexers, routers, VOD servers (video on demand), broadcast servers and video quality measurement equipments. 
   The method determines the spatial extent of loss for INTRA predicted frames when the payload associated with the spatial information is encrypted. The method also determines the temporal propagation of loss, utilizing the INTER prediction information in a series of coded image when the payload associated with the temporal information is encrypted. The method also determines the percentage of access units that are affected by a packet loss in an encrypted environment. 
   A preferred embodiment of the present invention is illustrated in  FIGS. 1-7 . An embodiment of the present invention can be utilized in an IPTV delivery system such as that illustrated in  FIG. 1 . 
     FIG. 1  shows a typical IPTV distribution network  10  that includes IPTV Content Acquisition  12 , IPTV Management System  14 , IPTV Content Distribution  16  and IPTV Consumer  18 . Video Source  20 ,  22  is usually acquired in analog form and encoded in MPEG 1/2/4 format by a video encoder  24 ,  26  and sent to either a Video on Demand (VOD) server  28  or a Broadcast server  30 . The stream originating from the VOD or Broadcast servers  28 ,  30  may be encrypted by a DRM server  32 ,  34 . The servers  28 ,  30  encapsulate the content into a program stream for transport to a network core  36 . When used, the DRM servers  32 ,  34  encrypt the encapsulated content from the servers  28 ,  30  and then pass it on to the network core  36 . The network core  36  is a relatively higher bandwidth pipe. 
   An IPTV network  10  also includes a variety of management, provisioning and service assurance elements. The IPTV Management System  14  includes an Operation Support System (OSS)  38 , a Subscriber management system  40  and Application Servers  42  to create new value added services. At the edge of the server  44 , the content is stored in VOD Server  46  or Broadcast Server  48  that is located close to the consumer. The Broadcast Server  48  can also received local content from Broadcast Video Source  50  which is encoded in MPEG 1/2/4 format by Encoder  52 . Here again a DRM Server  54  can encrypt the transport stream output from the Broadcast Server  48 . A consumer accesses the content through a broadband access line  56 , which is preferably a Cable/DSL line  58 . A television is typically connected to a set-top box  60  that decodes the video stream to component output. 
   Various probes  64 ,  66 ,  68 ,  70  are deployed at potential encrypted and unencrypted locations in the network  10 . Probes  64 ,  66  are capable of collecting unencrypted VCL information  71  since they both have access to unencrypted transport streams. Probes  68 ,  70  are capable of collecting only encrypted network layer parameters  73 , since the transport stream is encrypted at both access locations. These probes send the VCL and network layer information to collector  72  to perform a correlation function, as described below. 
   A protocol stack for a packetized video stream is illustrated in  FIG. 2 . Media dependent attachment  74  is an Ethernet, Sonet, DS3, cable, or DSL interface. A PHY chip  76  does the media dependent packet processing. IP Layer  78  is the network layer that provides addressing for packet routing in the IPTV network  10 . A User Datagram Protocol (UDP)  80  is the transport layer that provides application level addressing for access ports. The video stream is encapsulated in the UDP/RTP or UDP layer  80 . The encoded video could be compressed in MPEG 1/2/4 and sent as MPEG transport stream  82 . The transport stream  82  contains the program information for audio, video and other information. Network Abstraction Layer  84  is typically present in H.264/AVC type of coding to seamlessly transport Video Coding Layer  86  information for transmission on the network  10 . Network values for measurement  88  are extracted at the MPEG transport stream  82  layer. Video Coding Layer information for measurement  90  is extracted at the Video Coding Layer  86  specific to each codec. A protocol stack that uses RTP  92  instead of MPEG2  82  to convey program and timing information is shown in  FIG. 3 . For all other layers, the protocol stack in  FIG. 3  is the same as the protocol stack depicted in  FIG. 2 . 
     FIG. 4  illustrates how packets are decoded to get a correlation timestamp  94 . Only one timestamp is exported for correlation. The correlation timestamp preference order is PCR, PTS/DTS, RTP and statistics generation time (shown top to bottom) based upon availability. MPEG2 TS packet  96  provides the PCR timestamp  98 . PES packet  100  provides the PTS/DTS timestamp  102 . RTP packet  104  provides RTP timestamp  106 . Statistics generation event  108  provides Statistics timestamp  110 . The generated timestamps  98 ,  102 ,  106 ,  110  are processed according to the above stated preference to produce a single timestamp  94 . 
     FIG. 5  illustrates the information  90  that is extracted from the Video Coding Layer  86  and transmitted as VCL parameters  112  to collector  72 . Input to the VCL Parameters  112  includes: Access Unit Information  116 ; a correlation time base  118 ; Intra/Inter predicted macroblocks type, size (4×4, 8×4, 8×8 16×16) and quantization  120 ; video coding standard specific information  122 ; resolution of the screen in terms of pixels for horizontal and vertical sizes  124 ; I/B/P slices and type  126 ; the aspect ratio of the video  120  from parsing the coding layer; and reference picture list/indices  130 . These parameters  112  are exported to the collector  72  at n (configurable) access units interval with the correlation time  118 . 
     FIG. 6  illustrates the parameters  132  that are extracted at the Network Layer at the encrypted location. The parameters  132  include: an episode loss instance counter  134  at the transport stream level; a length of episode loss counter  136  measures the length of losses (bursty or single); and a correlation time  138  for each episode loss event. All of the network parameters  132  are collected and exported upon the occurrence of a loss event to the collector  72  with the correlation time  138 . 
     FIG. 7  illustrates correlation module  140  inputs, VCL parameters coming from head end  142 , and network parameters coming from down stream  144 . The output, i.e. the correlated video stream  146 , refers to a single stream that has both VCL and network layer information and spatial and temporal loss extent computed. K 104 _macroblock  148  gives the percentage of macroblocks affected. K 104 _slice  150  gives the percentage of slices affected. K 104 _picture  152  gives the percentage of pictures affected. 
   The operation of a preferred embodiment will now be explained with reference to the above described elements. At the location of probe  64 —before the DRM servers  32 ,  34 —the following operations are performed and the identified parameters are exported to the collector  72  for every n number of access units, where n is configurable in the system. 
   Initialize flow information for every video flow
         Set E 100 =destination IP/port/program ID string;       

   Initialize variables for each access unit in the instance:
         Set correlation time range A 100  (low)=0; A 106  (high)=0   Set Resolution of picture A 103 =0;   Set sequence number A 101 =0; for every transport payload size (188 bytes) from the access unit base time, increment sequence number for the VCL content RBSP (Raw byte sequence packet) to the macroblock level for every payload size;   Set IDR (Instantaneous Decoder Refresh) access unit A 102 =0; if available.       

   For each slice in access unit initialize following variables:
         Set slice ID B 100 =0;   Set slice Type B 101 =unknown;   Set sequence number range for slice data to B 102 -B 103 =0.       

   For each macroblock per slice set the following:
         Set macroblock type C 100 =unknown; it will be set to INTRA or INTER prediction later;   Set macroblock size C 102 =0;   Set sequence number range for macroblock data to C 103 -C 107     Set reference index to the reference picture list to C 104 =0, this will index to the reference picture list associated with the n number of access units;   Set reference index to the macroblocks within reference picture to C 105 =0; this will be the macroblock index to the referring picture in the list;   Set a flag to indicate loss of macroblock to C 106 =false.       

   Initialize the reference picture list access units. For n number of access units a list of reference pictures are maintained, each reference picture structure will have following information associated with it:
         Set correlation time range D 100 (low)=0; D 104 (high)=0;   Set sequence number range for the access unit in the reference picture to D 102 =0.
 
For each macroblock within reference picture;
   Set sequence number range to D 103 =0;   Set a flag to indicate loss of the macroblock D 104 =false.       

   At every transport stream packet perform the following at the unencrypted probe  64  location:
         For every access unit delimiter, get correlation time source, in either PCR or PTS; the present TS payload is assumed to be encrypted in this environment and only PCR is available as the correlation source;   Set F 102 =flow ID string;   Set A 100 =last PCR base+(number of bits time since last PCR to access unit delimiter bit)*37; Assumes 27 MHz clock base;   Set A 106 =last PCR base +(number of bits time since last PCR to access unit end delimiter bit)*37;   For every 188 bytes of access unit data increment A 101 ;   For Slice Data RBSP start set B 102 =A 101     Set Slice Data end RBSP B 103 =A 101 ;   Set B 100 =slice_id;   Set B 101 =slice_type (I/B/P/SI/SP).   For every macroblock in slice set:
           Set B 101 =A 101  for macroblock start;   Set B 107 =A 101  for macroblock end;   Set C 102 =macroblock_size;   Set C 104 =reference_index_picture_list;   Set C 105 =reference_index_picture;   Set C 106 =false; If a loss is encountered set it to true;   Set C 108 =quantization value for the macroblock;   Add the access unit to reference picture list if the encoder indicates;   
           At every n access units interval export the above values (reference+access units information) to collector ( 72 ) with the flow.       

   Initialize the following flow information for every video flow at encrypted location:
         Set F 100 =destination IP/port/program ID string;   Set D 100 =0 to set PCR base of the lost TS packets—10 (configurable), this is to ensure that access unit boundary is matched;   Set D 101 -D 102 =0 to set the sequence number range for loss (burst or single);   Set D 103 =0 to set the loss event sequence number.       

   At every n (configurable) number of loss event (where a loss event is defined as an episode where a single or consecutive loss period lasts):
         Set D 100 =store 10 PCR values before loss;   Set D 104 =last PCR base+number of bits time (from last PCR base to first payload in TS where last loss occurred)*37;   Set D 103 =0; At every loss event increment D 103 ;   Set D 101 =D 103  start loss; and   Set D 102 =D 103  end of loss.
 
Export the above parameters to the collection point  72  with the flow information.
       

   At the collector  72  gather parameters from encrypted and unencrypted locations and store them for analysis. The following analysis is performed to compute the spatial and temporal duration, slices/macroblocks affected by a loss. 
   Configure the collector  72  with a flow mapping from encrypted probes  68 ,  70  to probes  64 ,  66  to match the IP/port from encrypted to the unencrypted. At every unencrypted status event from probes  64 ,  66  maintain a list of access units and their associated reference picture list for the configured flow ID, up to a preconfigured number of access units. At every encrypted status event from probes  68 ,  70  match the flow ID to configuration with the access unit lists (E 100 ); when a match with encrypted flow is found perform the following:
         For each loss event find the access unit boundary;   Match the best fit access unit start time A 100  with D 100  in both access unit and reference picture list;   Set G 100 =D 102 -D 101  as lost packets;   Set C 106 =true to indicate access unit loss;   K 101 ++ to indicate access unit loss counter;
 
For every access unit base go through every slice and macroblock in the access unit list and reference picture list. Find the slices affected (INTRA slices) by the loss by performing the following:
   Set do_more_slice=true;   While (do_more_slice)
           G 101 =B 103 −B 102 ;
               If (G 101 &gt;G 100 ) the loss is within the slice else Do_more_slice=true;   
               Set K 102 ++ to indicate slice loss;   Set G 102 =C 107 -C 103 ;   
           While (G 102 —)
           Set C 106 =true to indicate macroblock loss;   K 103 ++ to indicate macroblock loss;   Spatial/temporal loss extent K 104  is equivalent to the access unit where slices are intra/inter predicted and the macroblocks within the slices that are intra/inter predicted; i.e. K 104 _SLICE=(K 102 *100)/Total intra/inter predicted slices;   K 104 _macroblocks=(K 103 *100)/Total intra/inter predicted macroblocks;   K 104 _PICTURE=(K 101 *100)/Total intra/inter predicted access units.
 
If the slice or macroblocks are INTER predicted, the following procedure needs to be used to predict the macroblock from reference picture list to find if it was affected by loss. Within each slice go through the macroblocks if they are inter predicted;
   
           While (G 102 —)   Get index C 104 , C 105  of ref picture list;   If (reference_pic_list.macroblock flag C 106  is set to true)
           ++K 103 ; to indicate macroblock loss;   
               

   A quantization parameter can also be extracted from the macroblock information C 108 ; after a correlation match is done. Although an embodiment has been described in detail for purposes of illustration, various modifications may be made to each without departing from the scope and spirit of the invention.