Abstract:
Presented herein are systems, methods, and apparatus for real-time high definition television encoding. In one embodiment, there is a method for encoding video data. The method comprises estimating amounts of data for encoding a plurality of pictures in parallel. A plurality of target rates are generated corresponding to the plurality of pictures and based on the estimated amounts of data for encoding the plurality of pictures. The plurality of pictures are then lossy compressed based on the target rates corresponding to the plurality of pictures.

Description:
RELATED APPLICATIONS  
       [0001]     This application claims priority to and claims benefit from: U.S. Provisional Patent Application Ser. No. 60/681,635, entitled “METHOD AND SYSTEM FOR RATE CONTROL IN A VIDEO ENCODER” and filed on May 16, 2005. 
     
    
     FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT  
       [0002]     [Not Applicable] 
       MICROFICHE/COPYRIGHT REFERENCE  
       [0003]     [Not Applicable] 
       BACKGROUND OF THE INVENTION  
       [0004]     Advanced Video Coding (AVC) (also referred to as H.264 and MPEG-4, Part 10) can be used to compress digital video content for transmission and storage, thereby saving bandwidth and memory. However, encoding in accordance with AVC can be computationally intense.  
         [0005]     AVC uses temporal coding to compress video data. Temporal coding divides a picture into blocks and encodes the blocks using similar blocks from other pictures, known as reference pictures. To achieve the foregoing, the encoder searches the reference picture for a similar block. This is known as motion estimation. At the decoder, the block is reconstructed from the reference picture. However, the decoder uses a reconstructed reference picture. The reconstructed reference picture is different, albeit imperceptibly, from the original reference picture. Therefore, the encoder uses encoded and reconstructed reference (predicted) pictures for motion estimation.  
         [0006]     Using encoded and predicted pictures for motion estimation causes encoding of a picture to be dependent on the encoding of the reference pictures.  
         [0007]     Additional limitations and disadvantages of conventional and traditional approaches will become apparent to one of ordinary skill in the art through comparison of such systems with the present invention as set forth in the remainder of the present application with reference to the drawings.  
       BRIEF SUMMARY OF THE INVENTION  
       [0008]     Aspects of the present invention may be found in a system, method, and/or apparatus for controlling the bit rate while encoding video data, substantially as shown in and/or described in connection with at least one of the figures, as set forth more completely in the claims.  
         [0009]     These and other advantages and novel features of the present invention, as well as illustrated embodiments thereof will be more fully understood from the following description and drawings.  
     
    
     BRIEF DESCRIPTION OF SEVERAL VIEWS OF THE DRAWINGS  
       [0010]      FIG. 1  is a block diagram of an exemplary system for encoding video data in accordance with an embodiment of the present invention;  
         [0011]      FIG. 2  is a flow diagram for encoding video data in accordance with an embodiment of the present invention;  
         [0012]      FIG. 3  is a block diagram of a system for encoding video data in accordance with an embodiment of the present invention;  
         [0013]      FIG. 4  is a flow diagram for encoding video data in accordance with an embodiment of the present invention; and  
         [0014]      FIG. 5  is a block diagram of an exemplary video classification engine in accordance with an embodiment of the present invention.  
     
    
     DETAILED DESCRIPTION OF THE INVENTION  
       [0015]     Referring now to  FIG. 1 , there is illustrated a block diagram of an exemplary system  100  for encoding video data in accordance with an embodiment of the present invention. The video data comprises pictures  115 . The pictures  115  comprise portions  120 . The portions  120  can comprise, for example, a two-dimensional grid of pixels.  
         [0016]     The computer system  100  comprises a processor  105  and a memory  110  for storing instructions that are executable by the processor  105 . When the processor  105  executes the instructions, the processor estimates an amount of data for encoding a portion of a picture.  
         [0017]     The estimate of the amount of data for encoding a portion  120  of the picture  115  can be based on a variety of factors. In certain embodiments of the present invention, the estimate of the portion  120  of the picture  115  can be based on a comparison of the portion  120  of the picture  115  to portions of other original pictures  115 . In a variety of encoding standards, such as MPEG-2, AVC, and VC-1, portions  120  of a picture  115  are encoded with reference to portions of other encoded pictures  115 . The amount of data for encoding the portion  120  is dependent on the similarity or dissimilarity of the portion  120  to the portions of the other encoded pictures  115 . Examining the original reference pictures  115  for the best portions and measuring the similarities or dissimilarities can estimate the amount of data for encoding the portion  120 .  
         [0018]     The estimated amount of data for encoding the portion  120  can also include, for example, content sensitivity, measures of complexity of the pictures and/or the blocks therein, and the similarity of blocks in the pictures to candidate blocks in reference pictures. Content sensitivity measures the likelihood that information loss is perceivable, based on the content of the video data. For example, in video data, loss is more noticeable in some types of texture than in others. In certain embodiments of the present invention, the foregoing factors can be used to bias the estimated amount of data for encoding the portion  120  based on the similarities or dissimilarities to portions of other original pictures.  
         [0019]     Additionally, the computer system  100  receives a target rate for encoding the picture. The target rate can be provided by either an external system or the computer system  100  that budgets data for the video to different pictures. For example, in certain applications, it is desirable to compress the video data for storage to a limited capacity memory or for transmission over a limited bandwidth communication channel. Accordingly, the external system or computer system  100  budgets limited data bits to the video. Additionally, the amount of data encoding different pictures  115  in the video can vary. As well, based on a variety of characteristics, different pictures  115  and different portions  120  of a picture  115  can offer differing levels of quality for a given amount of data. Thus, the data bits can be budgeted accordingly to these factors.  
         [0020]     In certain embodiments of the present invention, the system  100  can estimate amounts of data for encoding each of the portions  120  forming the picture  115 . The target rate can be based on the estimated amounts of data for encoding each of the portions  120  forming the picture  115 .  
         [0021]     Based on the target rate for the pictures  115  and the estimated amount of data for encoding portions  120  of the picture, the picture is lossy encoded. The estimates are finding the relative bit distribution of where bits should go in each picture and between pictures. Lossy encoding involves trade-off between quality and compression. Generally, the more information that is lost during lossy compression, the better the compression rate, but, the more the likelihood that the information loss perceptually changes the portion  120  of the picture  115  and reduces quality.  
         [0022]     Referring now to  FIG. 2 , there is illustrated a flow diagram for encoding a picture in accordance with an embodiment of the present invention. At  205 , portions of the picture are classified. At  210 , a relative quantization parameter for encoding the portions of the picture is estimated. At  215 , a nominal quantization parameter for encoding the picture is received. At  220 , the portions of the picture are lossy encoded, based on the nominal quantization parameter and the relative quantization parameter for encoding the portion of the picture.  
         [0023]     Embodiments of the present invention will now be presented in the context of an exemplary video encoding standard, Advanced Video Coding (AVC) (also known as MPEG-4, Part 10, and H.264). A brief description of AVC will be presented, followed by embodiments of the present invention in the context of AVC. It is noted, however, that the present invention is by no means limited to AVC and can be applied in the context of a variety of encoding standards.  
         [0024]     Referring now to  FIG. 3 , there is illustrated a block diagram of an exemplary system  500  for encoding video data in accordance with an embodiment of the present invention. The system  500  comprises a picture rate controller  505 , a macroblock rate controller  510 , a pre-encoder  515 , hardware accelerator  520 , spatial from original comparator  525 , an activity metric calculator  530 , a motion estimator  535 , a mode decision and transform engine  540 , and an entropy encoder  555 .  
         [0025]     The picture rate controller  505  can comprise software or firmware residing on an external master system. The macroblock rate controller  510 , pre-encoder  515 , spatial from original comparator  525 , mode decision and transform engine  540 , spatial predictor  545 , and entropy encoder  555  can comprise software or firmware residing on computer system  100 . The pre-encoder  515  includes a complexity engine  560  and a classification engine  565 . The hardware accelerator  520  can either be a central resource accessible by the computer system  100  or at the computer system  100 .  
         [0026]     The hardware accelerator  520  can search the original predicted pictures for candidate blocks that are similar to blocks in the pictures  115  and compare the candidate blocks CB to the blocks in the pictures. The hardware accelerator  520  then provides the candidate blocks and the comparisons to the pre-encoder  515 .  
         [0027]     The spatial from original comparator  525  examines the quality of the spatial prediction of macroblocks in the picture, using the original picture and provides the comparison to the pre-encoder  515 .  
         [0028]     The pre-encoder  515  estimates the amount of data for encoding each macroblock of the pictures, based on the data provided by the hardware accelerator  520  and the spatial from original comparator  525 , and whether the content in the macroblock is perceptually sensitive. The pre-encoder  515  estimates the amount of data for encoding the picture  115 , from the estimates of the amounts of data for encoding each macroblock of the picture.  
         [0029]     The pre-encoder  515  comprises a complexity engine  560  that estimates the amount of data for encoding the pictures, based on the results of the hardware accelerator  520  and the spatial from original comparator  525 . The pre-encoder  515  also comprises a classification engine  565 . The classification engine  565  classifies intensity, persistence and certain content from the pictures that is perceptually sensitive, such as human faces, where additional data for encoding is desirable. The classification engine  565  is described in further detail with respect to  FIG. 5 .  
         [0030]     Where the classification engine  565  classifies certain content from pictures  115  to be perceptually sensitive, the classification engine  565  indicates the foregoing to the complexity engine  560 . The complexity engine  560  can adjust the estimate of data for encoding the pictures  115 . The complexity engine  565  provides the estimate of the amount of data for encoding the pictures by providing an amount of data for encoding the picture with a nominal quantization parameter Qp. It is noted that the nominal quantization parameter Qp is not necessarily the quantization parameter used for encoding pictures  115 .  
         [0031]     The picture rate controller  505  provides a target rate to the macroblock rate controller  510 . The motion estimator  535  searches the vicinities of areas in the reconstructed predicted picture that correspond to the candidate blocks CB, for predicted blocks that are similar to the blocks in the plurality of pictures.  
         [0032]     The search for the predicted blocks by the motion estimator  535  can differ from the search by the hardware accelerator  520  in a number of ways. For example, the reconstructed predicted picture and the picture can be full scale, whereas the hardware accelerator  520  searches original predicted pictures and pictures that are reduced scale. Additionally, the blocks can be smaller partitions of the blocks by the hardware accelerator  520 . For example, the hardware accelerator  520  can use a 16×16 block, while the motion estimator  535  divides the 16×16 block into smaller blocks, such as 4×4 blocks. Also, the motion estimator  535  can search the reconstructed predicted picture with ¼ pixel resolution.  
         [0033]     The spatial predictor  545  performs the spatial predictions for blocks. The mode decision &amp; transform engine  540  determines whether to use spatial encoding or temporal encoding, and calculates, transforms, and quantizes the prediction error E from the predicted block. The complexity engine  560  indicates the complexity of each macroblock at the macroblock level based on the results from the hardware accelerator  520  and the spatial from original comparator  525 , while the classification engine  565  indicates whether a particular macroblock contains sensitive content. Based on the foregoing, the complexity engine  560  provides an estimate of the amount of bits that would be required to encode the macroblock. The macroblock rate controller  510  determines a quantization parameter and provides the quantization parameter to the mode decision &amp; transform engine  540 . The mode decision &amp; transform engine  540  comprises a quantizer Q. The quantizer Q uses the foregoing quantization parameter to quantize the transformed prediction error.  
         [0034]     The mode decision &amp; transform engine  540  provides the transformed and quantized prediction error E to the entropy encoder  555 . Additionally, the entropy encoder  555  can provide the actual amount of bits for encoding the transformed and quantized prediction error E to the picture rate controller  505 . The entropy encoder  555  codes the quantized prediction error E into bins. The entropy encoder  555  converts the bins to entropy codes. The actual amount of data for coding the macroblock can also be provided to the picture rate controller  505 .  
         [0035]     Referring now to  FIG. 4 , there is illustrated a flow diagram for encoding video data in accordance with an embodiment of the present invention. At  605 , an identification of candidate blocks from original predicted pictures and comparisons are received for each macroblock of the picture from the hardware accelerator  520 . For each macroblock, the hardware accelerator  520  provides the best vector that predicts the macroblock and quality metrics, which indicate the quality of the prediction for each reference picture. At  610 , comparisons for each macroblock of the picture to other portions of the picture are received from the spatial from original comparator  525 . At  615 , the pre-encoder  515  estimates the amount of data for encoding the picture based on the comparisons of the candidate blocks to the macroblocks, and other portions of the picture to the macroblocks. The process described above is for a single macroblock. The estimated relative bit allocations for each macroblock may be calculated and the sum of the estimated relative bit allocations is the relative bit allocation for the picture.  
         [0036]     At  620 , the macroblock rate controller  510  receives a target rate for encoding the picture. At  625 , transformation values associated with each macroblock of the picture  115  are quantized with a quantization step size, wherein the quantization step size is based on the target rate and the estimated amount of data for encoding the macroblock.  
         [0037]     The embodiments described herein may be implemented as a board level product, as a single chip, application specific integrated circuit (ASIC), or with varying levels of the decoder system integrated with other portions of the system as separate components.  
         [0038]     The degree of integration of the encoder system may primarily be determined by speed and cost considerations. Because of the sophisticated nature of modern processor, it is possible to utilize a commercially available processor, which may be implemented external to an ASIC implementation.  
         [0039]     If the processor is available as an ASIC core or logic block, then the commercially available processor can be implemented as part of an ASIC device wherein certain functions can be implemented in firmware. For example, the macroblock rate controller  510 , pre-encoder  515 , spatial from original comparator  525 , activity metric calculator  530 , motion estimator  535 , mode decision and transform engine  540 , and entropy encoder  555  can be implemented as firmware or software under the control of a processing unit in the encoder  110 . The picture rate controller  505  can be firmware or software under the control of a processing unit at the master  105 . Alternatively, the foregoing can be implemented as hardware accelerator units controlled by the processor.  
         [0040]     Referring now to  FIG. 5 , a block diagram of an exemplary video classification engine is shown. The classification engine  565  comprises an intensity calculator  701 , a persistence generator  703 , a object detector  705 , and a quantization map  707 .  
         [0041]     The intensity calculator  701  can determine the dynamic range of the intensity by taking the difference between the minimum luma component and the maximum luma component in a macroblock.  
         [0042]     For example, the macroblock may contain video data having a distinct visual pattern where the color and brightness does not vary significantly. The dynamic range can be quite low, and minor variations in the visual pattern are difficult to capture without the allocation of enough bits during the encoding of the macroblock. An indication of how many bits you should be adding to the macroblock can be based on the dynamic range. A low dynamic range scene may require a negative QP shift such that more bits are allocated to preserve the texture and patterns.  
         [0043]     A macroblock that contains a high dynamic range may also contain sections with texture and patterns, but the high dynamic range can spatially mask out artifacts in the encoded texture and patterns. Dedicating fewer bits to the macroblock with the high dynamic range can result in little if any visual degradation.  
         [0044]     Scenes that have high intensity differentials or dynamic ranges can be given fewer bits comparatively. The perceptual quality of the scene can be preserved since the fine detail, that would require more bits, may be imperceptible. A high dynamic range will lead to a positive QP shift for the macroblock.  
         [0045]     For lower dynamic range macroblocks, more bits can be assigned. For higher dynamic range macroblocks, fewer bits can be assigned.  
         [0046]     The human visual system can perceive intensity differences in darker regions more accurately than in brighter regions. A larger intensity change is required in brighter regions in order to perceive the same difference. The dynamic range can be biased by a percentage of the lumma maximum to take into account the brightness of the dynamic range. This percentage can be determined empirically. Alternatively, a ratio of dynamic range to lumma maximum can be computed and output from the intensity calculator  701 .  
         [0047]     The persistence generator  703  can estimate the persistence of a macroblock based on the sum of absolute difference (SAD) from motion estimation, the consistency of neighboring motion vectors and the dynamic range of the luma component. A high persistence can have a relatively low SAD since it can be well predicted. Elements of a scene that are persistent can be more noticeable. Whereas, elements of a scene that appear for a short period may have details that are less noticeable. More bits can be assigned when a macroblock is persistent. Macroblocks that persists for several frames can be assigned more bits since errors in those macroblocks are going to be more easily perceived.  
         [0048]     A block of pixels can be declared part of a target region by the object detector  705  if enough of the pixels fall within a statistically determined range of values. For example in an 8×8 block of pixels in which skin is being detected, an analysis of color on a pixel-by-pixel basis can be used to determine a probability that the block can be classified as skin.  
         [0049]     When the object detector  705  has classified a target object, quantization levels can be adjusted to allocate more or less resolution to the associated block(s). For the case of skin detection, a finer resolution can be desired to enhance human features. The quantization parameter (QP) can be adjusted to change bit resolution at the quantizer in a video encoder. Shifting QP lower will add more bits and increase resolution. If the object detector  705  has detected a target object that is to be given higher resolution, the QP of the associated block in the quantization map  707  will be decreased. If the object detector  705  has detected a target object that is to be given a lower resolution, the QP of the associated block in the quantization map  707  will be increased. Target objects that can receive lower resolution may include trees, sky, clouds, or water if the detail in these objects is unimportant to the overall content of the picture.  
         [0050]     The classification engine  565  can determine relative bit allocation. The classification engine  565  can elect a relative QP shift value for every macroblock during pre-encoding. Relative to a nominal QP the current macroblock can have a QP shift that indicates encoding with quantization level that is deviated from an average. A lower QP (negative QP shift) indicates more bits are being allocated, a higher QP (positive QP shift) indicates less bits are being allocated.  
         [0051]     The QP shift for intensity, persistence, and block detection can be independently calculated. The quantization map  707  can be generated a priori and can be used by a rate controller during the encoding of a picture. When coding the picture, a nominal QP will be adjusted to try to stay on a desired “rate profile”, and the quantization map  707  can provide relative shifts to the nominal QP.  
         [0052]     When encoding video, a target bit rate may be desired. However, not all pictures should be allocated the same number of bits. For example, the number of bits per picture will vary by type of picture (I, P or B) and by picture content or complexity. In a distributed system where many parallel processors are used to encode pictures, it is desirable to determine bit allocation prior to encoding the picture. To determine bit allocation a-prior, bit estimation and allocation may be performed in a pipelined fashion before encoding.  
         [0053]     Video quality is a function of a quantization parameter (QP). A constant QP yields roughly a constant peak signal to noise ratio (PSNR) in the reconstructed picture.  
         [0054]     To figure out the relative bit allocations of the pictures, a QP offset map and an estimate of the number of bits at each QP is determined.  
         [0055]     The QP offset map classifies areas to determine which parts of pictures should be encoded at higher quality and which can be encoded at a lower quality. The QP offset map at the macroblock level is applied as the encoding and bit estimates are made.  
         [0056]     The estimate of the number of bits needed to encode the picture at a fixed base QP adjusted by the classification map may be based on open loop spatial estimation and coarse motion estimation. The spatial mode and resulting prediction error (or optionally transformed and quantized prediction error) may be used to estimate the number of bits it would take to spatially encode the macroblock. The error resulting from the coarse motion estimation of the original pictures (or optionally, the transformed and quantized prediction error from this operation) may be used to estimate the number of bits it would take to spatially encode the macroblock. The smaller of these two estimates is used for the macroblock. The sum of all the smallest final estimates for all the macroblocks is the estimate for the picture. The rate control allocates bits in proportion to the variations in estimates such that the desired bit rate is obtained.  
         [0057]     The rate control also estimates the base QP for the picture based on the estimated number of bits at the tested QP and adapts the base QP to what is actually happening and also generates a map at the macroblock level of where the bits should go in the picture. The macroblock level rate control starts with the base QP and adds the offset map generated by the classification engine and a feedback QP to generate the final QP to use when encoding each macroblock. The feedback QP offset is a function of how the encoding rate is relative to the sum of the target bit allocations in the macroblock level rate map.  
         [0058]     The open loop spatial estimation does not require the actual reconstructed data. Therefore, the open loop spatial estimation breaks the dependence of one picture on another at the pre-encode stage. During the final encoding, the real spatial encoding requires the actual reconstructed data.  
         [0059]     In a similar way, the pre-encoding motion estimation may be performed on the original data to break the dependence on reconstructed data to generate an estimate of how to allocate bits. The final encoding differs from the estimates in the following ways: the final choice of modes includes evaluation of smaller partition sizes in inter coding; the mode selection may involve actual encoding to test the actual numbers of bits; and the predicted data is always from reconstructed pictures.  
         [0060]     It will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the scope of the present invention.  
         [0061]     Additionally, many modifications may be made to adapt a particular situation or material to the teachings of the present invention without departing from its scope. For example, although the invention has been described with a particular emphasis on the AVC encoding standard, the invention can be applied to a video data encoded with a wide variety of standards.  
         [0062]     Therefore, it is intended that the present invention not be limited to the particular embodiment disclosed, but that the present invention will include all embodiments falling within the scope of the appended claims.