US20020172288A1 - Device and method for performing half-pixel accuracy fast search in video coding - Google Patents

Device and method for performing half-pixel accuracy fast search in video coding Download PDF

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Publication number
US20020172288A1
US20020172288A1 US09/801,584 US80158401A US2002172288A1 US 20020172288 A1 US20020172288 A1 US 20020172288A1 US 80158401 A US80158401 A US 80158401A US 2002172288 A1 US2002172288 A1 US 2002172288A1
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pixel
value
sub
mad
lowest
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Nyeongku Kwon
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Lambert Everest Ltd
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AVT AUDIO VISUAL TELECOMMUNICATIONS Corp
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Priority to US09/801,584 priority Critical patent/US20020172288A1/en
Assigned to AVT AUDIO VISUAL TELECOMMUNICATIONS CORPORATION reassignment AVT AUDIO VISUAL TELECOMMUNICATIONS CORPORATION ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: KWON, NYEONGKU
Priority to US10/471,085 priority patent/US7792191B2/en
Priority to AU2002240754A priority patent/AU2002240754A1/en
Priority to PCT/CA2002/000324 priority patent/WO2002071741A2/en
Priority to JP2002570523A priority patent/JP4739651B2/ja
Publication of US20020172288A1 publication Critical patent/US20020172288A1/en
Assigned to LAMBERT EVEREST LTD. reassignment LAMBERT EVEREST LTD. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: AVT AUDIO VISUAL TELECOMMUNICATIONS CORPORATION
Priority to JP2008244850A priority patent/JP2009027744A/ja
Priority to JP2009230638A priority patent/JP2010045816A/ja
Priority to US12/877,109 priority patent/US20110064138A1/en
Abandoned legal-status Critical Current

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    • 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
    • H04N19/50—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding
    • H04N19/503—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding involving temporal prediction
    • H04N19/51—Motion estimation or motion compensation
    • H04N19/523—Motion estimation or motion compensation with sub-pixel accuracy

Definitions

  • the present invention relates to motion estimation algorithms for video compression and, in particular, to a device and method for performing a half-pixel accuracy fast search algorithm in video coding.
  • HDTV digital and high definition television
  • video conferencing video conferencing
  • computer imaging computer imaging
  • high quality video tape recorders Uncompressed digital video signals constitute a huge amount of data and therefore require a large amount of bandwidth and memory to store and transmit.
  • one of the formats defined for HDTV broadcasting within the United States is 1920 pixels horizontally by 1080 lines vertically, at 30 frames per second. If these numbers are all multiplied together, along with eight bits for each of the three primary colors, the total data rate required will be approximately 1.5 Gb/sec.
  • each channel only supports a data rate of 19.2 Mb/sec, which is further reduced to 18 Mb/sec because the channel must also support audio, transport, and ancillary data information.
  • the original signal must be compressed by a factor of approximately 83:1.
  • Digital compression devices are commonly referred to “encoders”, while devices that perform decompression are referred to as “decoders”. Devices that perform both encoding and decoding are often referred to as “codecs”.
  • MPEG moving picture experts group
  • Motion picture video sequences consist of a series of still pictures or “frames” that are sequentially displayed to provide the illusion of continuous motion.
  • Each frame may be described as a two-dimensional array of picture elements or “pixels”.
  • Each pixel describes a particular point in the picture in terms of brightness and hue.
  • Methods have been devised to reduce the amount of transmission data required to represent each frame. The reduction of transmission data is referred to as data compression.
  • compression methods Rather than transmitting large amounts of information for each pixel location's color and brightness, compression methods divide each frame into a predetermined number of “macroblocks”.
  • the macroblocks are typically defined as a 16 ⁇ 16 array of pixels. Since there is some similarity within and between successive frames, it is more efficient to transmit only the differences between the frames.
  • the motion vectors are determined by comparing each pixel location in the current macroblock with each pixel location in a successive reference frame.
  • the integer location which differs the least between the two macroblocks is used to generate the motion vector.
  • the process of searching every pixel location is referred to as a full or exhaustive search and the process of searching less than every pixel location is referred to as a fast search.
  • a fast search algorithm for integer pixel locations is described in U. S. Pat. No. 6,128,047 entitled “Motion Estimation Process And System Using Sparse Search Block-Matching And Integral Projection”, to Chang et al.
  • the current macro block does not always shift an integer number of pixels in a given direction in real world video encoding.
  • the macro block may be displaced by a fractional portion of a pixel.
  • Several methods exist which obtain the integer pixel location previously determined by a Full or Fast search integer pixel search algorithm and perform a second search on all 8 surrounding half-pixel locations to more accurately define the motion vector. While this yields a more accurate motion vector, there is an increase in the number of computations necessary to locate the correct half-pixel location.
  • 1 ⁇ 2 pixel search algorithms that perform a fast search, i.e., not all 8 1 ⁇ 2 pixel locations are searched.
  • f(i, j) represents a block of 16 ⁇ 16 pixels (macroblock) from the current frame
  • g(i, j) represents the same macroblock but from a reference frame (either previous or future in time)
  • the reference macroblock is displaced by a vector (dx, dy), representing the search location.
  • the MAD function calculates which integer pixel location in a succeeding frame contains a minimum difference. This pixel value becomes the integer pixel displacement value for a motion vector.
  • the Lee article describes how the 1 ⁇ 2 pixel points surrounding the previously determined integer pixel location are tested.
  • the surrounding half-pixel integer locations are separated into a horizontal and vertical pair.
  • Horizontal half-pixel points 2 and 7 and vertical half-pixel points 4 and 5 are interpolated based upon the surrounding integer pixel values and the MADs of location 2 as compared with location 7 , and location 4 as compared with location 5 to determine a minimum MAD pair.
  • the interpolated pixels are determined using MPEG approved bi-linear interpolation techniques.
  • the block with the lowest MAD value is then compared with the blocks of the opposing pairs to determine a minimum pair.
  • the minimum MAD pair is to be 2 and 5 and point 4 is additionally considered for half-pixel motion prediction.
  • the half-pixel accuracy motion vector is determined by comparing the MADs of the centered integer pixel block, the minimum candidate block, and the most recently considered point.
  • a half-pixel accuracy fast search algorithm in video coding that performs a hierarchical search method for motion estimation which initially searches for an integer accuracy motion vector and then continues its search having a sub-pixel accuracy over surrounding, reconstructed conjugate sub-pixels of the integer motion vector.
  • FIG. 1 is a graphical depiction of integer pixel and half-pixel locations according to the prior art
  • FIG. 2 is a graph depicting integer and half integer locations for interpolation
  • FIG. 3 is a graphical depiction of the surrounding half-pixel locations around an integer pixel location
  • FIG. 4 is a graphical representation of the half-pixel accuracy fast search algorithm according to the present invention.
  • FIG. 5 is a flow chart illustrating the half-pixel accuracy fast search algorithm in video coding according to the present invention
  • FIG. 6 is a diagram of a system consistent with the present invention.
  • FIGS. 7 - 10 are graphical representations of the peak signal to noise ratio (PSNR) performance of the present invention with test video stream inputs.
  • PSNR peak signal to noise ratio
  • Motion picture video sequences consist of a series of still pictures or “frames” that are sequentially displayed to provide the illusion of continuous motion.
  • Each frame may be described as a two-dimensional array of picture elements, or “pixels”.
  • Each pixel describes a particular point in the picture in terms of brightness and hue.
  • Pixel information can be represented in digital form and displayed on a monitor such as a High Definition television, or encoded, and broadcast.
  • the novel component is called entropy and it is the true information in the signal.
  • the remainder is called redundancy because it is not essential and may be recreated from other frames. Redundancy may be spatial, as it is in large plain areas of the picture where adjacent pixels have almost the same value. Redundancy can also be temporal, as it is where similarities between successive pictures are used. Compression systems work by separating the entropy from the redundancy in the encoder. The entropy is recorded or transmitted along with motion vectors which describe redundant data. The decoder uses the entropy data and redundancy data to generate complete frames to display.
  • An ideal encoder transmits the entropy of a sequence of frames and recreates the additional redundant information using previous or subsequent frames of redundant pixel information without any loss of image quality.
  • the higher the compression ratio the more prone the signal transmission is to digital artifacts or errors, thus reducing signal quality. Since ideal encoders do not presently exist, there is a balancing between compression ratio and signal quality.
  • Intracoding is a technique that exploits spatial redundancy, or redundancy within the picture while interceding is a technique that exploits temporal redundancy, or redundancy between successive pictures.
  • Intracoding is a technique that exploits spatial redundancy, or redundancy within the picture
  • interceding is a technique that exploits temporal redundancy, or redundancy between successive pictures.
  • Two types of motion estimation methods are typically used to estimate the motion vectors; pixel-recursive algorithms and block-matching algorithms.
  • Pixel-recursive techniques predict the displacement of each pixel from corresponding pixels in neighboring frames.
  • Block matching algorithms estimate the displacement between frames on a block-by-block basis and choose displacement vectors that minimize the difference. The entire macroblock is then displaced by the motion vector.
  • the current image to be encoded is divided into equally sized blocks of pixel information. These “macro blocks” typically consist of a 16 ⁇ 16 sample array of luminance samples together with 18 ⁇ 8 block of samples for each of the two chrominance components.
  • Block matching motion estimation algorithms are generally categorized as either a full search or a fast search algorithm based on its search strategy.
  • Full search also known as the exhaustive search, computes the error between successive macro blocks at all possible candidate integer pixel locations in order to find the motion vector of the macro block. While it is simple in complexity to implement, it carries an extensive computational burden to search the entire area of each macro block and successive macro block locations. Hence, many fast search algorithms have been proposed that reduce the amount of integer pixel locations to search for a minimum error between successive macro blocks.
  • the present invention proposes a hierarchical approach having sub-pixel accuracy.
  • the term hierarchical connotes that the algorithm first calculates a minimum integer pixel location and then performs a sub-integer pixel search.
  • the present invention obtains the integer pixel value with the lowest MAD value and then interpolates conjugate half-pixel values in a first direction.
  • the algorithm determines which half-pixel value yields the lowest MAD value and then interpolates conjugate half-pixel values in a second direction from the previously calculated minimum MAD half-pixel location from the first direction.
  • This conjugate search method described reduces the calculations performed by the conventional half-pixel search methods from eight to four half-pixel locations.
  • a two-dimensional reconstructed image using interpolation is described in a mathematical expression as follows, where two-dimensional convolution is conducted between sampled pixel image and interpolation function.
  • B(.) is the reconstructed interpolation image and ⁇ overscore (B) ⁇ (.) and h(.) are sampled pixel image and interpolation filter function respectively.
  • FIG. 2 is a graph depicting integer and half integer locations for use with bilinear interpolation.
  • Bilinear interpolation is a process by which half-pixel values are determined and has been adopted by MPEG as the standard for calculating half-pixel values.
  • half-pixel values a, b, c, d and e are calculated as follows:
  • A, B, C, and D are integer-pixels and a, b, c, d, and e are surrounding half-pixels.
  • the half pixel values are used by the present invention in determining a half pixel accuracy motion vector.
  • FIG. 3 is a graphical representation of the surrounding half-pixel locations around an integer pixel location.
  • half-pixel locations 1 through 8 which surround an integer pixel location zero are calculated using, for example, the formulas previously described.
  • FIG. 4 shows a graphical representation of an integer location zero surrounded by multiple half-pixel locations 1 through 8 respectively.
  • an example of possible search locations for the half-pixel accuracy fast search algorithm in video coding according to the present invention are described with reference to I Left , I Center , I Right , and II Center , II Top , and II Bottom .
  • the fast half-pixel search first calculates an integer pixel location in a macroblock which has a minimum MAD value using a known integer pixel full or fast search algorithm. Once that integer pixel location is calculated, the conjugate half-pixel values in a first direction I Left and I Right are determined. For example, assume the first direction is horizontal and parallel to an X-axis of a 2 dimensional grid. The MADs of I Left and I Right are calculated and the half-pixel location with the lowest MAD value is stored. Conjugate half-pixel values in a second direction are also calculated starting from the previously stored pixel location having the lowest MAD value. Based upon the above, presume the second direction is in a vertical direction and parallel to a y-axis of a grid.
  • the first and second directions are perpendicular to each other.
  • II Top and II Bottom are determined. Note that I Right I Center or I Left will be equal in value to II Center when the first and second directions are perpendicular to each other.
  • MAD values for those two locations are determined.
  • the half-pixel location having the lowest MAD value is also stored and used as an offset for the integer pixel value previously determined. Accordingly, a new motion vector combining integer pixel location l center plus the half-pixel location having the minimum MAD value are used to generate a final motion vector for displacing the macroblock.
  • the motion vector MV(x, y) is defined as:
  • MV ( x,y ) MV integer ( x,y )+ d h ( x,y ) (2)
  • MV integer (x, y) is the integer accuracy motion vector
  • d h (x, y) is the half-pixel displacement
  • the method may also compare the integer location with the conjugate sub-pixel locations to determine the location having the lowest MAD value.
  • a half-pixel motion estimation algorithm operating according to the present invention yields more accurate motion displacement information than an integer pixel motion vector and reduces the computations required in a full search from 8 to 4 , thereby reducing the computations by 50%.
  • search order could be performed in a vertical direction followed by a horizontal direction, the particular order being a matter of design choice.
  • first direction could be diagonally from top right to bottom left and the second direction could be from bottom right to top left. The conjugate values being determined with respect to the diagonals.
  • FIG. 5 is a flow chart illustrating a half-pixel accuracy fast search in a video coding example according to the present invention.
  • First perform an initial integer search using a previously known integer search algorithm and determine the motion vector MV integer (x, y).
  • Step 500 performs a sub-pixel conjugate interpolation in a first direction.
  • Step 505 calculate MAD values for each of the conjugate sub-pixel locations in the first direction D(x+1, y), and D(x ⁇ 1, y), where the second direction variable y is fixed.
  • Step 510 Next determine a minimum MAD value in the first direction.
  • Step 515 determines a minimum MAD value in the first direction.
  • Step 520 perform sub-pixel conjugate interpolation in a second direction centered on the sub-pixel location having the minimum MAD value in the first direction.
  • Step 520 calculate MAD values for the conjugate sub-pixel locations in the second direction D(x, y+1) and D(x, y ⁇ 1) where the x variable is fixed.
  • Step 525 determine the minimum MAD value in the second direction.
  • Step 530 Calculate a new motion vector based upon the sub-pixel location having the minimum MAD value.
  • Step 535 set the motion vector for the macroblock equal to the sum of the motion vector for the integer pixel plus the motion vector for the sub-pixel location.
  • Step 540 set the motion vector for the macroblock equal to the sum of the motion vector for the integer pixel plus the motion vector for the sub-pixel location.
  • FIG. 6 is a diagram of a system 600 consistent with the present invention.
  • System 600 is comprised of a central processing unit (“CPU”) 605 , a random access memory (“RAM”) 610 , a read only memory (“ROM”) 620 and a computer readable medium 625 interconnected via a system bus 670 .
  • Computer readable medium 625 contains computer readable instructions necessary to perform the half-pixel accuracy fast search according to the present invention and may be embodied as, but not limited to, any media that provides instructions according to the present invention to CPU 605 for execution. Examples of computer readable medium may be RAM, ROM, Electrically Erasable Programmable ROM (“EEPROM”), CD-ROM, or transmission medium such as Network connections, Radio Waves, or other wireless information transmission means.
  • EEPROM Electrically Erasable Programmable ROM
  • An input/output (I/O) signal 660 is connected to system 600 and may provide an input stream of Audio/Video data to compress or decompress.
  • CPU 605 accesses I/O signal 660 along with instructions contained in medium 625 to determine the correct half-pixel accuracy motion vectors as described above.
  • CPU 605 may receive image data from an input device 650 or display I/O signal 660 on a display 630 . Once the image data is received via input device 650 or I/O signal 660 and processed via CPU 605 , the image data can be either stored on a storage device 675 or transmitted via a transmitter and antenna 680 .
  • System 600 as well as medium 625 may be incorporated into many devices including, but not limited to, Motion video recorders, Digital Video Disk recorders (“DVDs”), Satellite and television transmitters and receivers, Video Display cards for personal computers and other MPEG compliant devices, to reduce the amount of information required to transmit digital video information and reduce the amount of calculations required to obtain accurate motion vectors.
  • DVDs Digital Video Disk recorders
  • Satellite and television transmitters and receivers Video Display cards for personal computers and other MPEG compliant devices
  • PSNR peak signal to noise ratio
  • N is the number of pixels
  • O 1 and R 1 are the amplitudes of the original and the reconstructed pixels.
  • Both half-pixel search methods show better performance with the difference of up to 2dB in average PSNR compared to the integer-pixel search method. In comparison of both half-pixel search methods, those methods, fast and full search, do not show much difference in terms of PSNR with all of four video sequences, while the required number of computation as described in the present invention was reduced to half of the full search method.
  • Table 2 shows the computer simulation data of the present invention with comparison to integer-pixel full search, fast search, and half-pixel full search in terms of the number of computations.
  • the processing speed improvement of the present invention is clearly shown in the simulation data, especially when it is involved in integer-pixel fast search algorithm.
  • the portion of total half-pixel search points is approximately 1% of the total number of points searched during an integer-pixel full search.
  • the number of computations performed during the conventional half-pixel full search becomes even larger than the one of integer-pixel fast search.
  • Table 1 indicates that the present invention improved the processing speed by reducing the number of required.
  • the simulation data shows about 30% reduction in the overall number of computations required and a 50% reduction compared to the conventional half-pixel full search.
  • FIGS. 7 - 10 present the PSNR data of each picture frame from 100 frames with four test video sequences.
  • the full half pixel search, the fast half pixel search according to the present invention and the integer pixel search are compared in each of the graphs.
  • the full half pixel search and the fast half pixel search according to the present invention are almost overlapping each other showing similar performance with respect to the PSNR, however, the integer pixel search, remains below the other two fast search data with up to 2dB PSNR difference. Therefore, the present invention reduces the number of computations required to generate a half-pixel accurate motion vector by 50% while experiencing only a negligible amount of noise as compared to the full half pixel search.

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US09/801,584 US20020172288A1 (en) 2001-03-08 2001-03-08 Device and method for performing half-pixel accuracy fast search in video coding
US10/471,085 US7792191B2 (en) 2001-03-08 2002-03-08 Device and method for performing half-pixel accuracy fast search in video coding
AU2002240754A AU2002240754A1 (en) 2001-03-08 2002-03-08 A device and method for performing half-pixel accuracy fast search in video coding
PCT/CA2002/000324 WO2002071741A2 (en) 2001-03-08 2002-03-08 A device and method for performing half-pixel accuracy fast search in video coding
JP2002570523A JP4739651B2 (ja) 2001-03-08 2002-03-08 ビデオ符号化における中間画素高精度高速探索を実現する装置及び方法
JP2008244850A JP2009027744A (ja) 2001-03-08 2008-09-24 ビデオ符号化における中間画素高精度高速探索を実現する装置及び方法
JP2009230638A JP2010045816A (ja) 2001-03-08 2009-10-02 ビデオ符号化における中間画素高精度高速探索を実現する装置及び方法
US12/877,109 US20110064138A1 (en) 2001-03-08 2010-09-08 Device and method for performing half pixel accuracy fast search in video coding

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