US20100271554A1 - Method And Apparatus For Motion Estimation In Video Image Data - Google Patents

Method And Apparatus For Motion Estimation In Video Image Data Download PDF

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US20100271554A1
US20100271554A1 US12/677,507 US67750708A US2010271554A1 US 20100271554 A1 US20100271554 A1 US 20100271554A1 US 67750708 A US67750708 A US 67750708A US 2010271554 A1 US2010271554 A1 US 2010271554A1
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motion
field
vector
line
motion vectors
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Volker Blume
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Entropic Communications LLC
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N7/00—Television systems
    • H04N7/01—Conversion of standards, e.g. involving analogue television standards or digital television standards processed at pixel level
    • H04N7/0127—Conversion of standards, e.g. involving analogue television standards or digital television standards processed at pixel level by changing the field or frame frequency of the incoming video signal, e.g. frame rate converter
    • H04N7/0132—Conversion of standards, e.g. involving analogue television standards or digital television standards processed at pixel level by changing the field or frame frequency of the incoming video signal, e.g. frame rate converter the field or frame frequency of the incoming video signal being multiplied by a positive integer, e.g. for flicker reduction
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • G06T7/246—Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N7/00—Television systems
    • H04N7/01—Conversion of standards, e.g. involving analogue television standards or digital television standards processed at pixel level
    • H04N7/0135—Conversion of standards, e.g. involving analogue television standards or digital television standards processed at pixel level involving interpolation processes
    • H04N7/014—Conversion of standards, e.g. involving analogue television standards or digital television standards processed at pixel level involving interpolation processes involving the use of motion vectors
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10016—Video; Image sequence

Definitions

  • the present invention is related to a method and an apparatus for motion estimation in video image data and especially for field rate up-conversion motion estimation video image data.
  • the present invention is further related to a TV-set, a computer program product and a data carrier comprising a computer program.
  • the present invention relates to a motion estimation and motion compensation device and more particularly to a motion estimation and motion compensation device that estimates motion vectors and performs motion compensated predictions of an interlaced sequence of chrominance sub-sampled video frames.
  • FIG. 1 wherein the motion trajectory of the moving objects (white squares) in the original image fields (i.e. transmitted and received image fields) is supposed to be straight-lined. If the missing fields result from interpolation by means of the above mentioned standard FRU methods (i.e. without motion estimation and compensation), the motion of the moving object in the interpolated fields (dark grey squares) is not at a position as expected by the observer (dotted squares). Such artefacts are visible and induce a blurring effect especially of fast moving objects. These blurring effects typically reduce the quality of the displayed images significantly.
  • This MEMC provides the detecting of a moving part or object within the received image fields and then the interpolation of the missing fields according to the estimated motion by incorporating the missing object or part in an estimated field.
  • FIG. 2 shows schematically the change of the position of a moving object between two successive image fields.
  • the moving objects will have changed their position, e.g. object MO which is in the previous field T in position A is then in the current field T+1 then in position B.
  • This motion of an object in successive image fields can be represented by a so-called motion vector.
  • the motion vector AB represents the motion of the object MO from position A in the previous field T to position B in the current field T+1.
  • This motion vector AB typically has a horizontal and a vertical vector component. Starting from point A in the previous field T and applying this motion vector AB to the object MO the object MO is then translated in position B in the current field T+1.
  • the missing position I of the object MO in the missing field T+1 ⁇ 2 that has to be interpolated must be calculated by the interpolation of the previous field T and the current field T+1 taken account of the respective positions A, B of the moving object MO. If the object MO does not change its position between the previous field and the current field, e.g. if A and B are the same positions, position I in the missing field is obtained by the translation of A with a motion vector
  • a first approach employs a so-called block-based MEMC.
  • This approach assumes that the dimension of an object in the image is always larger than that of a single pixel. Therefore, the image field is divided into several image blocks. For MEMC only a single motion vector is calculated for each one of these blocks which leads to a significant reduction of used motion vectors. This approach is for example described in EP 874 523 A1.
  • a second approach employs a so-called line-based MEMC.
  • the algorithms is based on a reduced set of video input data of a single line of a field or part of this line.
  • this line based MEMC there is so far no method known in the art for an effective reduction of motion vectors.
  • the present invention is, therefore, based on the object to provide a possibility to more efficiently use motion vectors within a motion estimation process.
  • the present invention is further based on the object to reduce the memory requirement and/or the computational requirements in motion estimation implementations.
  • a method comprising the features of claim 1 and/or an apparatus comprising the features of claim 15 and/or a TV-set comprising the features of claim 23 and/or a computer program product comprising the features of claim 24 and/or a data carrier comprising the features of claim 25 is/are provided.
  • motion vectors are calculated which are suitable for being used in a subsequent motion compensation process.
  • the calculation of the motion vector might be performed for every pixel of a frame or a field, or alternatively for only some of these pixels, e.g. several selected pixels within a line or part of a line. It is also possible that this motion vector is assigned to a predefined block or section of a frame or a field.
  • One basic idea of the present invention is the provision of a motion vector histogram which contains information which of the calculated motion vectors is used mostly and which is even rarely used in a current frame or field of a picture.
  • This information stored in the motion vector histogram enables a significant and effective motion estimation process and thus also an efficient motion compensation process since only part of the calculated motion vectors is used. This consequently reduces the overall memory requirement and computational effort significantly.
  • Another advantage of the present invention is the fact, that the whole motion estimation and motion compensation process is getting more and more quick which is especially in modern video applications one of the key issue for the establishment of a highly precise picture of the TV-panel.
  • the present invention describes also a method for motion estimation and motion compensation which operates only in one direction and therefore performs the motion estimation and motion compensation operations using at least one single line buffer memory, the so-called line memory.
  • This offers the possibility to reduce the chip embedded memory to one single line memory for the previous and one single line memory for the current field or frame. This advantageously enables significant silicon area reducing and cost saving implementations.
  • the MEMC is limited to motion in the horizontal direction only, since most of the motion in natural scenes has this direction.
  • video signal processing line memories are often used in other applications which already have access to the previous and current motion portrayal, e.g. like so-called de-interlacer applications or temporal noise reduction applications.
  • these already existing line memories of the video application are now additionally used also for MEMC operations.
  • this solution offers the possibility to accomplish the MEMC operations by adding a minimal or in the optimal case no additional memory to the video processing system.
  • the method is used for line-based motion estimation.
  • the motion vector having the highest rank and/or are the most often used motion vectors is/are selected.
  • the method further comprises a motion compensation wherein the selected motion vector is used for motion compensation to interpolate a picture.
  • the motion vectors having the highest rank and/or the most often used motion vector are stored in a memory.
  • the step of calculating a histogram is done for the whole frame or field.
  • the step of calculating a histogram is done for parts of the frame or field by splitting the frame or field into horizontal stripes and detect most often used vector for each stripe.
  • the step of calculating a histogram is done to detect news ticker information, sub-titles or any other written information within a frame or field.
  • a damping value which depends on the selected motion vector is used to adapt motion vectors with similar counter values.
  • the histogram information of the rank of an motion vector is used to detect reliable and unreliable motion vectors.
  • the motion vector contains only motion data for motion of an object in one direction and especially in the horizontal direction.
  • image data of the previous frame is derived from a first line memory and image data of the current frame is derived from a second line memory.
  • first line memory and/or the second line memory is/are further used in a de-interlacer application and/or a temporal noise reduction application.
  • a histogram generator is provided to establish a motion vector histogram for motion vectors to derive most and less used motion vectors in a current frame or field.
  • the apparatus further comprises a histogram generator to provide a motion vector histogram for motion vectors to derive most and less used motion vectors in a current frame or field.
  • the histogram generator further comprises a counting device for counting the occurrences of identical motion vector by incrementing or decrementing the counter by a given value; a ranking device which is designed to compare different counter values assigned to the different motion vectors and which is further designed to rank the different motion vectors on the basis of their occurrence in a current frame or field and to selects the most often used motion vector for the motion compensation.
  • a motion vector histogram memory is provided to store the most often used motion vectors.
  • a first line memory for storing image data of the previous frame and a second line memory for storing image data of the current frame are provided.
  • first line memory and/or the second line memory are configured to be further used in a de-interlacer device and/or a temporal noise reduction device.
  • the apparatus is an integrated circuit and/or is implemented within a microcontroller or a microprocessor.
  • FIG. 1 shows the result of a standard (i.e. non motion compensated) FRU method
  • FIG. 2 shows the change of position of a moving object between two consecutive received image fields
  • FIG. 3 show the motion estimation principle for the line-based motion estimation by means of a current frame and the corresponding previous frame
  • FIG. 4 shows a block diagram of a first embodiment of a line-based MEMC system according to the present invention
  • FIG. 5 shows an example to illustrate the matching process of the motion estimation
  • FIG. 6 shows the basic principle for the provision of a motion vector histogram
  • FIG. 7 shows a block diagram illustrating an embodiment of the line-based motion estimation according to the present invention.
  • FIG. 8 shows a block diagram illustrating an embodiment of the line-based motion compensation according to the present invention using adaptive artefact concealments
  • FIG. 9 shows a block diagram of a second embodiment of a line-based MEMC system according to the present invention using the line memories assigned to the de-interlacer device also for the motion estimation device.
  • the MEMC method consists mainly of two sections, the motion estimation and the motion compensation method.
  • the motion estimation performs the measurement of the motion and derives the velocity of the displayed regions in pixel per picture (i.e. field or frame). Also the direction of the motion will be indicated by a positive or negative sign. These measured motion information is described in the form of a motion vector.
  • the motion vector is used for the motion compensation to interpolate the picture at the temporal accurate position and to avoid so-called judder effects and/or so-called motion blurring effects.
  • FIG. 3 shows the motion estimation principle for the line-based motion estimation by means of a current picture (field or frame) 10 ( n ) and the corresponding previous picture 11 ( n ⁇ 1).
  • the motion vector 12 , 13 will be split by its length into two parts, where the first vector part 12 points into the previous picture 11 and the second vector part 13 points into the current picture 10 .
  • 11 pixels 15 from both temporal pictures 10 , 11 are taken into account for the compensation.
  • line-based MEMC only the pixels 15 within the same line 16 are used at the same time and the MEMC is performed for a single line 16 of a field or frame only.
  • the pixels 15 of the current picture 10 are compared with the corresponding pixels 15 of the previous picture 11 to estimate and compensate the corresponding pixels 15 of the missing picture 14 .
  • FIG. 4 shows a block diagram of a line-based MEMC system according to the present invention.
  • the MEMC system is denoted by reference number 20 .
  • the MEMC system 20 comprises an input terminal 21 , a bus 22 , two line memories 23 , 24 , a motion estimation device 25 , a motion compensation device 26 and an output terminal 27 .
  • the bus 22 is an external bus 22 and especially an external memory bus 22 .
  • the bus 22 is an internal bus 22 .
  • the bus 22 is connected to an external memory 28 device such as a SDRAM, a DDR-RAM, etc.
  • Image data to be displayed in a panel 29 such as a plasma- or LCD-panel or a CRT-screen is stored in this external memory 28 .
  • this image data X 1 , X 1 ′ is transferred to both line memories 23 , 24 .
  • the first line memory 23 is used for buffering image data X 1 of the previous picture and the other line memory 24 is used for storing the image data X 1 ′ of the current picture.
  • a line memory 23 , 24 as used in the present patent application indicates an embedded memory of a size of one video line of a frame or a field or at least less of the incoming video signal stream or actually processing video signal stream.
  • a field denotes a video image or picture which comprises either odd or even lines.
  • a frame denotes a video image comprising of the complete video information for one picture, i.e. of a field for the odd lines and the corresponding field for the even lines.
  • a line denotes a full horizontal row within a field of one video picture or at least a part of this row.
  • Both of the line memories 23 , 24 are coupled—on their output sides—to the motion estimation device 25 and to the motion compensation device 26 .
  • This enables the image data X 1 , X 1 ′ stored in the line memories 23 , 24 to be transferred to the motion estimation device 25 and to the motion compensation device 26 , respectively.
  • the corresponding data signals to the motion estimation device 25 are denoted by X 2 , X 2 ′ and the corresponding data signals motion compensation device 26 are denoted by X 3 , X 3 ′.
  • the motion estimation device 25 generates a motion vector signal X 4 out of the image data X 2 , X 2 ′ stored in the line memories 23 , 24 by employing a matching process.
  • This vector signal X 4 is transferred to the motion compensation device 26 .
  • the motion compensation device 26 performs a motion compensation using the image data X 3 , X 3 ′ stored in the line memories 23 , 24 and applying the vector data X 4 to this image data X 3 , X 3 ′.
  • the motion compensation device 27 provides a video signal X 5 which comprises information for a motion compensated picture.
  • This video signal X 5 is transferred via the output terminal 27 to a display 29 , such as a LCD-panel 29 or the like.
  • a matching process is employed to select a corresponding series of pixels 32 which fits best to a given amount of pixels 30 .
  • a given amount of pixels 30 of a line of a current frame around the centre pixel 31 for which the motion shall be determined is taken from a line memory 24 of the current frame 32 .
  • this given amount of pixels 30 is denoted to as series of pixels 30 .
  • a series of pixels 30 comprises 9 single pixels 33 . It is self-understood that a series can also comprise a greater or a smaller amount of pixels 33 .
  • Luminance is a photometric measure of the density of luminous intensity in a given direction. It describes the amount of light that passes through or is emitted from a particular area, and falls within a given solid angle. Thus, luminance is the photometric measure of the brightness in a frame of a motion picture. If the luminance is high, the picture is bright and if it is low the picture is dark. Thus, luminance is the black and white part of the picture.
  • This luminance profile is used to find out that series of nine pixels 34 out of the previous frame 35 which fits best with the series of nine pixels 30 of the current frame 32 .
  • the luminance profile of the series of nine pixels 30 of the current frame 32 are compared with the luminance profiles of several corresponding series of nine pixels 34 of the previous frame 35 .
  • the series of nine pixels 30 will be shifted over the search range in the horizontal direction 36 . It is assumed that that series of nine pixels 34 of the previous frame 35 which shows the best luminance profile matching (with the series of nine pixels 30 of the current frame 32 ) is the correct series of pixels. These series of pixels 30 , 34 are then used for the computation of the motion vector.
  • a typical value for the search range is, e.g. 64 pixels (+31 . . . ⁇ 32). However, it may also be possible to use less than 64 pixels, however, then the quality of the result of this comparison is increasingly going down. On the other hand it is also possible to use more than 64 pixels. Then the quality of the selection result is going up, however, this needs more computational effort. Therefore, typically a trade-off which provides an optimization between best quality of the selection result and simultaneously a minimum computation effort is employed.
  • SAD sum of absolute difference
  • the matching process can then be performed more efficiently if a set 38 of pre-selected motion vectors 37 —the so-called motion vector samples 37 —are checked for a matching of the luminance profile (see FIG. 5 ).
  • a set 38 of pre-selected motion vectors 37 the so-called motion vector samples 37 —are checked for a matching of the luminance profile (see FIG. 5 ).
  • one selected motion vector 37 can be taken from the neighbouring pixel.
  • a second selected motion vector can be taken from the previous line, if the already estimated motion vectors are stored in a vector memory specially designed for the different motion vector samples.
  • the zero-vector which indicates no motion of the object is typically one of the most used motion vector samples. This zero-vector is used in order to more efficiently detect regions within a picture showing no motion. In principle the amount of pre-selected motion vectors 37 which will taken into account depend strongly on what kind of motion vector quality is desired.
  • a variation of certain pre-selected motion vectors is required for test operation purposes. That means that for pre-selected motion vector samples a certain amount of motion will be added or subtracted. This can be done by applying a variance with different amount of motion speed to these motion vectors.
  • the tested implementation checks between odd pixels and even pixels alternating an update of +/ ⁇ 1 pixels and +/ ⁇ 4 pixels on the previously determined motion vector.
  • the selection of the variance is adjustable and variable as required or as the need arises and depends e.g. on the resolution of the incoming video signal.
  • the selection of the tested motion vectors is treated differently for the first line of a frame or field.
  • the selected motion vectors which normally test the motion vectors of the line above are loaded with vector values, which e.g. vary according to a triangle function from pixel to pixel.
  • the triangle function oscillates between an adjustable minimum value and an adjustable maximum value.
  • other regular oscillating functions e.g. a saw tooth function, a sinusoidal function, and the like may be employed for the determination of the motion vector of the first line.
  • the matching process assigns a failure value to each tested motion vector.
  • this value may be also a quality value. It might also be possible to evaluate as well a failure value and a quality value for the matching process.
  • the sum of the absolute difference (SAD) is used as the failure value or to at least derive the failure value.
  • SAD absolute difference
  • a failure value of zero is needed. However, typically the failure value is different from zero. Therefore, the motion vector corresponding with the lowest failure value is then selected as the most probably motion vector representing the motion of an object in the local scene.
  • a damping value is used which depends on the vector attenuation of the different motion vectors. This enables to control the motion vectors with equal failure values and/or to furnish the motion vector selection process with a certain direction.
  • the different motion vectors are advantageously stored in a vector memory. These motion vectors can be then—if required—fetched from the vector memory for further processing and/or for the motion estimation of the next pixels.
  • the motion estimation process forms a recursive process. Therefore, the size of this vector memory mainly depends on the desired quality level of the matching process.
  • the tested implementation comprises only one line of a vector memory. In this vector memory every second motion vector will be stored alternately, in order that an access of the motion vectors from the measured line above is possible.
  • a motion vector histogram is calculated in order to create a highly reliable and homogeneous field of motion vectors. This vector histogram allows a vector majority ranking to derive most and less used motion vectors in an actual scene.
  • FIG. 6 shows a preferred embodiment to illustrate the basic principle for the provision of a motion vector histogram accordingly to the present invention.
  • FIG. 6 shows a vector histogram generator 40 to provide a motion vector histogram.
  • the vector histogram generator 40 comprises a switching device 41 , which is controlled by an +1-incrementing device 42 .
  • the switching device 41 is controlled on the one hand by a motion vector 43 information and on the other hand by the incrementing device 42 which shift the switching device 41 to the next input terminal of a counting device 45 whensoever the next identical motion vector 43 occurs.
  • the counting device 45 which comprises different counter cells 44 counts the occurrence of each motion vector and increments the counter by +1 for each occurrence of the motion vector.
  • a ranking device 46 which e.g. comprises a simple comparing means—is coupled to the output terminals of the different counter cells 44 of the counting device 45 .
  • This ranking device 46 selects the most often used motion vector and applies this motion vector for the estimation determination.
  • the most often used motion vector may be then stored in a motion vector histogram memory 47 .
  • a motion vector histogram can be done either for the whole frame or field or only for parts of the frame or field. It is very efficient to split the picture into horizontal stripes and return a most often used vector for each stripe. In very a preferred embodiment news ticker information within a picture can be detected in that way very reliable.
  • FIG. 7 shows a block diagram illustrating an embodiment of the line-based motion estimation according to the present invention as described above and as implemented in a motion estimation device 25 as shown in FIG. 4 .
  • the motion estimation device 25 comprises a matching device 80 , a cost/quality function device 81 and a vector selector device 82 , which are arranged in series connection between the input side 83 of the motion estimation device 25 where the image data signals X 1 , X 1 ′ stored in the both line memories 23 , 24 are provided and the output side 84 of the motion estimation device 25 where the motion vector signal X 4 in present.
  • a matching process and a vector selection as described with regard to FIG. 5 is implemented.
  • the motion estimation device 25 further comprises a vector quality device 85 which is connected on the one hand to the input side 83 and on the other hand to the output side 84 .
  • the vector quality device 85 generates a quality signal X 6 comprising an information of the vector quality out of the image data signals X 1 , X 1 ′ and the motion vector signal X 4 .
  • the motion estimation device 25 further comprises a vector histogram device 86 and a vector majority device 87 which are arranged in series connection in a feedback path between the output side 84 and the matching device 80 .
  • a vector histogram is generated to provide a ranking of most and less used vectors in the actual scene as shown and described with regard to FIG. 6 .
  • the elements 86 , 87 correspond to the vector histogram generator 40 of FIG. 6 .
  • the motion estimation device 25 may further comprise a further line memory 88 to store the motion vector data X 4 and/or the data X 6 for the vector quality.
  • the motion estimation device 25 further comprises a vector sample device 89 .
  • This vector sample device 89 is also arranged in the feedback path and is connected at its input side with the line memory 88 , the vector majority device 87 and advantageously with a further device 90 .
  • This further device 90 performs a variation of the motion vector samples by using a special signal having a certain magnitude, e.g. a sinusoidal signal, a saw tooth signal or the like. This certain signal is then used for a testing and/or matching process and/or an up-dating process of the first line of a frame or field. However, it might also be possible to randomly up-date different lines of the frame or field.
  • the vector sample device 89 On its output side, the vector sample device 89 is connected at its output side to the matching device 80 .
  • the motion estimation device 25 further comprises a vertical motion estimation device 91 .
  • a vertical motion estimation device 91 For vertical motions the above described one-dimensional motion estimation algorithm is not able to compensate fully motion in the vertical direction. However, the occurrence of vertical motions can be used to reduce the compensation in same regions of the picture by splitting the picture into different regions to derive vertical motion for each region. In this case the luminance values of the lines in the different region of the same picture will be summed up and stored individually for each line of this picture. This results in an accumulated vertical profile for different regions of the same picture. Then, the whole picture can be divided into smaller regions to derive a vertical motion for each of these regions. This vertical motion estimation process is performed in the vertical motion estimation device 91 which is connected to the input side 83 and which provides at its output side a sector based vertical motion index X 7 .
  • the vertical MEMC as sketched above can be performed independently of horizontal MEMC and also in combination with the horizontal MEMC, wherein the combination can be performed in dependence on a certain situation or the motions present, respectively. Further, such a methodology allows an implementation of vertical MEMC, which does not need large amounts of additional memory capacity to analyze data of consecutive frames being the case in the most methodologies of the prior art.
  • the motion estimation device 25 further comprises a vector damping device 92 .
  • a damping value as described above may be used to damp vector samples of the vector sample device 89 and to provide damped vector samples to the vector selector 82 .
  • FIG. 8 shows a block diagram illustrating an embodiment of the line-based motion compensation according to the present invention using adaptive artefact concealments as described above.
  • the motion compensation device 26 comprises a compensation device 100 which performs the temporal motion interpolation according to the motion vectors X 4 estimated by the motion estimation device 25 .
  • the compensation device 100 comprises a Median Filter which uses as input data the luminance values of the vector compensated previous line, the vector compensated current and the uncompensated previous line. Additionally, also the chrominance values can be compensated.
  • a replacement vector indicated as reliable vector will be searched in the local area of the vector memory from the line above. If no reliable vector can be found the adaptive blurring typically tries to cover this artefact.
  • the motion compensation device 26 further comprises a vertical motion control device 101 which provides a control signal X 8 to the compensation device 100 in order to incorporate also information of a vertical motion to the compensation device 100 .
  • the motion compensation device 26 further comprises a bad vector modification device 102 . Based on information X 4 , X 6 provided by the motion estimation device 25 the bad vector modification device 102 modifies bad vectors. These information X 9 about modified bad vectors is then used—together with the control signal X 8 —to perform the motion compensation within the compensation device 100 . The compensation device 100 then generates at its output side a motion compensated image data signal X 10 .
  • the motion compensation device 26 further comprises an adaptive blurring device 103 . Based on the motion compensated image data signal X 10 and a blurring control signal generated by the bad vector modification device 102 this adaptive blurring device 103 performs an adaptive blurring.
  • the adaptive blurring device 103 generates an adaptive blurred image data signal X 5 ′ which might correspond to the image signal X 5 of FIG. 4 .
  • FIG. 9 shows a block diagram of a second embodiment of a line-based MEMC system according to the present invention using the line memories assigned to the de-interlacer device also for the motion estimation device.
  • a de-interlacer device 113 is arranged between the line memories 110 , 111 , 112 and the motion compensation device 26 .
  • the de-interlacer device 113 is typically used to convert a field represented by video data stream into a full frame which is then also represented by another video data stream.
  • On-chip solutions for video processing which are memory-based have already existing internal line buffers 110 - 112 —the so-called line memories 110 - 112 —which carry video data from the previous and current field or frame.
  • These line buffers 110 - 112 can be located e.g. within temporal noise reductions or de-interlacing units 113 which operate motion adaptive.
  • these line buffers can be reused additionally for the motion estimation.
  • a movie detector which indicates the current interpolated sequence of pull-down mode is used.
  • a line buffer selector transfers the video signal data to the motion estimation device according to the previous and the current video input signal. This technique allows using already existing memory resources also for motion estimation which also prevents additional bandwidth for the temporal up-conversion process. Therefore, the chip area for the motion estimation and the motion compensation can be reduced to a minimum.
  • the de-interlacer device 113 uses three line memories 110 , 111 , 112 coupled on their input side to the memory bus 22 and providing at their output side line data.
  • This line data provided by the line memories 110 , 111 , 112 is processed within the de-interlacer device and then provided to the motion compensation device 26 .
  • these line memories 110 , 111 , 112 are additionally used also for the motion estimation device 25 .
  • the system 20 additionally comprises a selector device 114 , where a movie sequence X 0 is provided to this selector device 114 .
  • This movie sequence X 0 may be then stored in an external memory 28 via the memory bus 22 and can be read out from this external memory 28 through the line memories 110 , 111 , 112 .
  • this data stored in the line memories 110 , 111 , 112 of the de-interlacer device 113 can be also used for MEMC.
  • the data stored in the line memories 110 , 111 , 112 is then provided as well to the motion estimation device 25 and the motion compensation 26 device.
  • the present invention is not based necessarily on so-called line-based MEMC systems, although in the above embodiments of the present invention always reference is made on line-based MEMC systems.
  • the present invention is related generally to all implementations using motion estimation of video image data, i.e. especially so-called block-based motion estimation, line-based motion estimation and the like. It is self understood that for those implementations which do not apply line-based motion estimation typically other memory means than line memories maybe employed.

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