KR20060064509A - Apparatus for motion estimation of image data - Google Patents

Abstract

The present invention discloses an image motion estimation apparatus.

According to the present invention, a SAD calculator which receives image data and calculates a SAD value of each frame of an image, divides each frame of the image data into macroblocks and submacroblocks of a predetermined size, and then macroblocks and submacroblocks. A motion vector calculator that calculates a motion vector estimate using motion vectors and prediction vectors of neighboring macroblocks or submacroblocks, and a SAD calculator for neighboring macroblocks or submacroblocks of predetermined size macroblocks and submacroblocks. A motion estimator for estimating the motion of the image data using the SAD value and the motion vector estimator of the motion vector calculator, which can estimate motion with reference to a neighboring block, can be compared to a conventional motion estimation device. The size and economic cost of the device required to implement the Im has an effect capable of operating with low power consumption for the estimation.

Description

Apparatus for motion estimation of image data}

1 illustrates an example of a conventional motion estimation apparatus.

2 is a block diagram illustrating a configuration of an apparatus for estimating video motion according to the present invention.

3 is a block diagram illustrating an example of a configuration of an image motion estimation apparatus according to the present invention, including a peripheral configuration thereof.

4A to 4I are diagrams for describing a process of performing calculation for each mode according to the present invention.

The present invention relates to image data compression, and more particularly, to an apparatus for estimating motion of an image.

FIG. 1 is a block diagram illustrating an example of a conventional motion estimation device, in particular, a motion estimation device combining an OPGS (One-Pixel Greedy Search) algorithm and a HSBM (Hierarchical Search Block Matching) algorithm.

Referring to FIG. 1, a conventional motion estimation apparatus includes a candidate vector predictor 100, an algorithm selector 110, a motion estimator 120, a memory 130, and a half-pixel motion estimator 140. It is configured by.

The candidate vector predictor 100 receives image data and predicts a candidate vector for a macro block to be estimated currently. In this case, the candidate vector predictor 100 finally selects a motion vector that is most optimally matched among the zero motion vector, the previous motion vector, and the motion vectors of neighboring blocks as the candidate motion vector.

The algorithm selector 110 selects a motion estimation algorithm by comparing a sum of absolute difference (SAD) of the candidate vector predicted by the candidate vector predictor 100 with a preset threshold. That is, one of the OPGS algorithm and the HSBM algorithm is selected by the algorithm selecting unit 110.

The motion estimation unit 120 performs forward pixel motion estimation of the input image data and outputs a motion vector according to the motion estimation unit 120. The algorithm used is an OPGS algorithm or an HSBM algorithm selected by the algorithm selection unit 110.

The memory 130 stores the motion vector output by the motion estimator 120 and applies the motion vector to the candidate vector predictor 100. The half-pixel motion estimation unit 140 estimates the half-pixel motion of the macro block and the sub block from the image data input by referring to the position of the positive pixel motion estimation value estimated by the motion estimation unit 17.

In the conventional motion estimation apparatus of FIG. 1, when the motion vector is predicted and the prediction value is included in the threshold range, the motion estimation operation is performed only on a search area smaller than the search area according to the OPGS algorithm, and the prediction value is When not included in the threshold range, the motion estimation operation is performed on the entire search area according to the HSNM algorithm, thereby increasing the efficiency of motion estimation.

However, since the conventional motion estimation apparatus has a separate independent memory corresponding to each algorithm, a large amount of computation is required during motion estimation, and thus there is a problem that it is not easy to apply the motion estimation apparatus to the real-time video encoder. In addition, since the conventional motion estimation apparatus must include an additional memory for storing a motion vector therein, there is a limit to the area occupied by the device and reduction of power consumption. In addition, since a fixed algorithm is used, it is difficult to provide an efficient result by performing unnecessary operations according to the type and application of the image.

The technical problem to be solved by the present invention is to provide an apparatus capable of efficient motion estimation.

According to an aspect of the present invention, there is provided an apparatus for estimating motion, comprising: a SAD calculator configured to receive image data and calculate SAD values of respective frames of an image; Each frame of the image data is divided into macroblocks and submacroblocks of a predetermined size, and motion vector estimates are calculated by using motion vectors and prediction vectors of macroblocks or submacroblocks around the macroblocks and submacroblocks. A motion vector calculator; And estimating the motion of the image data by using the SAD value calculated by the SAD calculator of the neighboring macroblock or submacroblock of each predetermined size and the submacroblock and the motion vector estimation value of the motion vector calculator. Motion update unit; characterized in that it comprises a.

H.264 is a standard that is jointly developed by VCEG of ITU and MPEG of ISO, a group of international video standards. The standard has a very high compression ratio as the main technical goal. It is a general purpose video encoding technology that can be used in almost all transmission media such as storage media, Internet, satellite broadcasting, and various video resolutions.

Traditionally, ITU's international standards have established video coding standards such as H.261 and H.263, which are based on wired communication media. MPEG is MPEG-1 and MPEG- for video processing in storage media and broadcasting media. 2 etc. were established as a standard. MPEG also completed the development of the MPEG-4 video standard, which realizes various functions and high compression ratios, which are important features of object-based video coding in MPEG-4, a multimedia standard coding standard.

ITU's VCEG group has been developing a high compression video standard under the name H.26L since the MPEG-4 video standard was established. In an official comparison experiment in MPEG, the MPEG-4 video standard (advanced simple profile) It showed a greater advantage in terms of compression ratio. Accordingly, MPEG decided to develop H.264 / AVC, a JVT video standard, in collaboration with ITU VCEG Group based on H.26L. H.264 / AVC has various excellent characteristics, but the method of determining the optimal coding mode among them contributes greatly to the performance improvement.

The optimal coding mode determination module is a part for determining an encoding mode of a macroblock which is a basic unit of encoding, and motion estimation is located at the core thereof. As a feature, a macroblock may be divided into submacroblocks or subblocks of various shapes, and each subblock may have a separate motion vector. In addition, unlike conventional motion estimation method using only one reference image, a large number of reference images can be used to obtain a significant compression efficiency. However, these features lead to an increase in computation. Therefore, the motion estimation algorithm in H.264 / AVC should be designed in consideration of the side of prediction error and the side of calculation.

The present invention may operate in the H.264 standard, and technical parts that are not separately described in the following description may be regarded as operating according to the H.264 standard, and a separate description may be omitted.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

2 is a block diagram illustrating a configuration of an apparatus for estimating video motion according to the present invention. The apparatus receives an image data and calculates the SAD value of each frame of the image SAD calculation unit 200, each frame of the image data is divided into macroblocks and sub-macroblocks of a predetermined size, each macroblock and sub A motion vector calculator 210 that calculates a motion vector estimate using a motion vector and a prediction vector of a macroblock or a submacroblock around a macroblock, and a neighboring macroblock or subblock for each macroblock and submacroblock of a predetermined size. The motion updater 220 estimates the motion of the image data by using the SAD value calculated by the SAD calculator 200 and the motion vector estimated value of the motion vector calculator 210 for the macroblock.

3 is a block diagram illustrating an example of a configuration of an image motion estimation apparatus according to the present invention, including a peripheral configuration thereof.

The input data, which is image data, is stored in the memory unit 330 at an address corresponding to the address value generated by the address generator 340, and the stored image data is input to the SAD calculator 300.

The motion updater 320 divides the SAD-calculated image into macroblocks composed of 16x16 pixels and updates the motion. The 16x16 mode calculation unit 322 and the 16x16 macroblocks each have 16x8 pixel sized macroblocks. 16x8 mode calculation unit 324 for dividing and updating motion, 8x16 mode computation unit 326 for updating motion by dividing 16x16 macroblocks into 8x16 pixel subblocks, respectively, and 8x8 pixel size respectively. The 8x8 mode calculating unit 328 updates the motion by dividing into sub-macroblocks.

Image data is stored in the memory unit 330, and the data is transferred from the memory unit 330 to the SAD calculator 300 and from the SAD calculator 300 and the motion vector calculator 310 to the motion updater 320. The transfer process is executed by the control of the controller 350. The control unit 350 is connected to the bus so that the motion estimation apparatus according to the present invention can exchange data with the system.

The image data is stored in the memory unit 330, and may be stored in units of frames at this time. Alternatively, the image data stored in the memory unit 330 may be input to the SAD calculator 300 in units of frames.

The SAD calculator 300 receives image data and calculates SAD, which is a sum of all absolute values of the difference between pixels between two blocks for each macroblock included in a frame. At this time, in accordance with the mode of the motion updater 220, SAD is calculated for not only 16x16 macroblocks but also 16x8, 8x16 and 8x8 submacroblocks included in the macroblocks.

The SADs for the macroblocks or sub-macroblocks for each size as described above are transmitted to the corresponding mode calculators 322 to 328 of the motion updater 320.

In addition, the image data stored in the memory unit 330 is also transferred to the motion vector calculator 310. In FIG. 3, the connection between the memory unit 330 and the motion vector calculator 310 is omitted to show a connection relationship with other components.

The motion vector calculator 310 calculates motion vectors of 16x16 macroblocks included in each frame of the image data and submacroblocks of 16x8, 8x16 and 8x8 sizes included in the macroblocks.

The motion estimation apparatus according to the present invention can be regarded as a relationship dependent on the function of determining the encoding mode. This is because a SAD (Sum of Absolute Difference) or SATD (Sum of Absolute Transform Difference) and a motion vector are used in the encoding mode decision process.

In the high complexity mode used in the present invention, a rate-distortion (RD) optimization technique is used by introducing a concept of a bit amount required for encoding, which is not considered in the low complexity mode. The high complexity mode is used to obtain better compression and error prevention performance when the complexity is not a problem, for example, when sufficient computational power is given.

The motion vector calculator 310 calculates an optimal motion vector using a rate distortion (RD) optimization technique as shown in the following equation.

In Equation 1 above, the notation SA (T) D represents SAD or SATD .

움직임 벡터이며,At this time

Is a motion vector,

예측 벡터이고,

Is a prediction vector,

는 Lagrangian 계수

이다.

Lagrangian modulus

to be.

The motion vector is for the current macroblock or submacroblock, and the prediction vector is a prediction vector obtained by referring to data for a block before the current split block. s is a reference image and c represents a current image. That is, c (m) represents a motion vector with respect to the current image.

는 최종적으로 부호화되어야 할 움직임 정보의 비트수이다. 이때에 R이 레이트 왜곡(Rate Distortion)의 정도이다. 즉,

는 움직임 벡터에서 예측 벡터를 뺀 벡터의 레이트 왜곡의 정도가 된다.And

Is the number of bits of motion information to be finally encoded. R is the degree of rate distortion at this time. In other words,

Is the degree of rate distortion of the vector minus the prediction vector.

At this time, SAD in Equation 1 is obtained as follows. This is executed by the SAD calculation unit 300.

Definitions of symbols used in Equation 2 are the same as those used in Equation 1.

In this case, m is a motion vector and when the first partition is a block, the macroblock or submacroblock, which is the first partition, has a random value or a value for a frame before or after the block to be referred to for motion prediction. It can also be used. In this case, m may be input from the outside from the position of the motion vector calculator 310.

In motion estimation, SATD, not SAD, is used for mode determination at the position of fractional pixels other than integer pixels. This is because H.264 / AVC also takes a technique of encoding transform coefficients after converting a residual signal like the existing international video encoding standard. That is, when the SAD calculated as described above is used as a criterion for mode determination, it may not be easy to obtain an optimal motion vector or spatial prediction mode because it does not fully reflect the characteristics of the transformed coefficients. For that. Therefore, the use of integer transform adopted by H.264 / AVC may be more effective in determining the optimal mode.However, in order to eliminate implementation complexity that may be caused by using SATD. A Hadamard transform having a Kernel as defined in Equation 3 is used. The Hadamard transform having the basis as defined in Eq. (3-6) is performed in two dimensions to obtain DiffT, and finally the SATD.

Using the basis defined in Equation 3, DiffT can be obtained as shown in Equation 4 below.

Where H [] is a Hadamard transform operator. The Hadamard transform is performed by performing the transform in the vertical and horizontal directions. Finally, the SATD is determined by the following equation.

을 최소화하는 움직임 벡터값을 구하여, 결과적으로 RD 최적화를 이용한 최적의 움직임 벡터를 구할 수 있다.Obtained as above

By obtaining a motion vector value that minimizes the result, an optimal motion vector using RD optimization can be obtained.

The SAD calculator 300 may divide a macroblock region of 16x16 pixel size of an image into four 8x8 submacroblock regions, and calculate an SAD for each 8x8 submacroblock region. If the SAD calculation value for the 8x8 submacroblock area is SAD8_8, the SAD values for each of the 4 submacroblock areas are SAD8_08 [0], SAD8_08 [1], SAD8_08 [2], and SAD8_08 [3]. Can be displayed separately. At this time, these four SAD calculated values can be expressed as SAD8_8 [0..3].

The SAD calculator 300 includes a module for calculating SAD8_8 [0..3] and a buffer module for storing the SAD8_8 [0..3], and includes a motion updater for SAD8_8 stored in each buffer module. Transfer to the calculation unit (322 to 328) for each mode of 320. Since such a buffer module stores four SAD8_8 per one candidate vector and supplies them to the motion updater 320 in parallel, the four mode calculators 322 to 328 included in the motion updater 320 as a result. Allow simultaneous operation.

The 16x16 mode calculation unit 322 is supplied with the result of adding all of SAD8_08 [0..3], the 16x8 mode calculation unit 324 is supplied with the result of adding SAD8_08 [0] and SAD8_08 [1], and SAD8_08 [ 2] and SAD8_08 [3] are then supplied. The 8x16 mode calculation unit 326 supplies the result of adding SAD8_08 [0] and SAD8_08 [2], and then supplies the result of adding SAD8_08 [1] and SAD8_08 [3]. The 8x8 mode calculation unit 328 supplies the results of SAD8_08 [0], SAD8_08 [1], SAD8_08 [2], and SAD8_08 [3] in this order.

In order to support the above-described block-by-block simultaneous operation, the present invention estimates the motion for each block simultaneously by using the motion vector for the submacroblock and the subblock, unlike the conventional art.

Conventionally, the motion vectors for the submacroblock and the subblock should be obtained sequentially to estimate the motion. For example, in the 16x8 split mode, the motion vector of the first 16x8 submacroblock must be determined to obtain the motion prediction vector of the second 16x8 submacroblock. For this reason, motion vectors for submacroblocks and subblocks cannot be obtained sequentially. This causes a serious problem in the implementation of the motion estimator. In order to improve the speed of the motion estimator, which occupies a large part of the encoder calculation amount, it is generally implemented in hardware. However, the motion estimator in the high complexity mode has a limitation in improving the speed of the motion estimator because it cannot perform motion estimation in parallel.

In order to solve this limitation, the present invention estimates the motion of the image data while simultaneously operating the calculation units 322 to 328 for each mode of the motion updater 320 using the positions of neighboring blocks.

4A to 4I are diagrams for describing a process of performing calculation for each mode according to the present invention. In the drawing, the bold parts indicate the boundaries of the macroblocks, and the thin parts indicate the boundaries of the blocks.

4A illustrates screens divided into macroblock units having a size of 16 × 16 pixels. The motion is estimated by the 16x16 mode calculator 322 in the divided units.

Based on the macroblock indicated by X in FIG. 4A, motion vector values of the previous image are motion vector values of macroblocks corresponding to positions A, B, and C, respectively. The motion is estimated by the median of these vectors. In this case, if block C is not valid, it is replaced with D, which is an upper block of A.

As described above, referring to neighboring macroblocks or submacroblocks when calculating motion vector estimates or estimating motions, the upper, upper right, and left-end ( It is preferable to refer to macroblocks or submacroblocks located at left) .When estimating the motion of an image included in a submacroblock, the following motion is estimated for all submacroblocks included in one macroblock. It is desirable to estimate the motion for the submacroblock included in the macroblock.

And when estimating the motion of the image included in the sub-macroblock sub-macroblocks of the upper, upper right and left sub-macroblock based on the current sub-macroblock is not motion estimation If there is a macroblock, the motion is estimated except for the submacroblock, and when the motion of the image included in the submacroblock is estimated, the upper, upper right, and If there is a submacroblock belonging to the macroblock to be processed after the macroblock including the current submacroblock among the left submacroblocks, the upper left submacroblock is excluded except for the submacroblock. It is desirable to estimate the motion by including.

4B and 4C illustrate a 16 × 16 macroblock divided into 16 × 8 subblocks. The 16x8 mode calculator 324 estimates the motion in units of the divided blocks. In the case of FIG. 4B, submacroblocks of A, B, and C are referred to for the current position X as shown in FIG. 4A. However, in the case of FIG. 4C, the subblock of C cannot be referenced with respect to the current position X. Since the motion estimation is performed on the X block after the motion estimation is performed on the subblock of B, no estimation is yet made on the submacroblock C.

4D and 4E illustrate macroblocks of 16x16 pixel size divided into 8x16 size. The 8x16 mode calculator 326 estimates the motion in units of this submacroblock. In this case, motion is estimated for each block in the same manner as in FIG. 4A.

4F to 4I illustrate a 16 × 16 macroblock divided into 8 × 8 subblocks. The 8x8 mode calculator 328 estimates the motion in units of the divided blocks.

In the case of FIGS. 4F to 4H, the motion is estimated by referring to neighboring blocks as in FIG. 4A, but in FIG. 4I, the motion is estimated by referring to the D submacroblock without referring to the C submacroblock for the current position X. . In the case of FIG. 4I, the motion is estimated for X after estimating the motion of the subblocks of blocks D, B, and A, and in this case, the motion of the subblock block of C is not yet estimated. It is not referenced in the estimation.

Since the values of neighboring regions have similarities due to the characteristics of the image, it can be seen that the motion estimation such as the present invention can obtain reliable results.

In addition, according to the present invention, if the vector value for motion estimation is obtained from the neighboring macroblock or the sub-macroblock, and applied to all the divided blocks, the structure of the apparatus for motion estimation is a high complexity, but the structure of the motion estimator in the low complexity mode It can be made similarly.

In addition, since the operation for motion estimation and the area or size of each block can be reduced through the present invention as described above, power required for device operation for motion estimation may be smaller than in the prior art, and thus, the mounting area may be reduced. Can

Those skilled in the art will appreciate that the present invention can be implemented in a modified form without departing from the essential features of the present invention. Therefore, the disclosed embodiments should be considered in descriptive sense only and not for purposes of limitation. Examples included in the above description are introduced for the understanding of the present invention, and these examples do not limit the spirit and scope of the present invention. It will be apparent to those skilled in the art that various embodiments in accordance with the present invention in addition to the above examples are possible. The scope of the present invention is shown in the claims rather than the foregoing description, and all differences within the scope will be construed as being included in the present invention.

In addition, it can be easily understood by those skilled in the art that each of the above steps according to the present invention can be variously implemented in software or hardware using a general programming technique.

According to the present invention, a SAD calculator which receives image data and calculates a SAD value of each frame of an image, divides each frame of the image data into macroblocks and submacroblocks of a predetermined size, and then macroblocks and submacroblocks. A motion vector calculator that calculates a motion vector estimate using motion vectors and prediction vectors of neighboring macroblocks or submacroblocks, and a SAD calculator for neighboring macroblocks or submacroblocks of predetermined size macroblocks and submacroblocks. A motion estimator for estimating the motion of the image data using the SAD value and the motion vector estimator of the motion vector calculator, which can estimate motion with reference to a neighboring block, can be compared to a conventional motion estimation device. The size and economic cost of the device required to implement the Im has an effect capable of operating with low power consumption for the estimation.

Claims (6)

A SAD calculator which receives the image data and calculates a SAD value of each frame of the image; Each frame of the image data is divided into macroblocks and submacroblocks of a predetermined size, and motion vector estimates are calculated by using motion vectors and prediction vectors of macroblocks or submacroblocks around the macroblocks and submacroblocks. A motion vector calculator; And A motion of estimating the motion of the image data using the SAD value calculated by the SAD calculator of the neighboring macroblock or submacroblock of each predetermined size and the submacroblock and the motion vector estimation value of the motion vector calculator; And an updater. The method of claim 1, The motion updater divides each SAD-calculated frame into a 16x16 pixel macroblock and the macroblock, and divides the macroblock into 16x8, 8x16, and 8x8 pixel sizes, and simultaneously extracts motion vector estimates for each block. Image motion estimation apparatus, characterized in that for calculating. The method of claim 2, Referencing neighboring macroblocks or submacroblocks when calculating the motion vector estimate or estimating the motion is based on the current macroblock or submacroblock, which is upper, upper right, and left. And a macroblock or a submacroblock located at the same. The method according to claim 2 or 3, When estimating the motion of the image included in the sub-macroblock, after estimating the motion for all sub-macroblocks included in one macroblock, the motion of the sub-macroblock included in the next macroblock is estimated. A video motion estimation device. The method of claim 4, wherein When estimating the motion of the image included in the sub-macroblock, the sub-blocks of which motion estimation is not performed among the upper, upper right, and left sub-macroblocks based on the current sub-macroblock. If there is a macroblock, the motion estimation apparatus of the image, characterized in that the motion is estimated by excluding the submacroblock. The method of claim 4, wherein When estimating the motion of the image included in the submacroblock, the current submacroblock is displayed among the submacroblocks of the upper, upper right, and left sides based on the current submacroblock. If there is a sub-macroblock belonging to a macroblock to be processed after the included macroblock, an image motion estimation apparatus comprising estimating motion by including an upper left sub-macroblock except for the sub-macroblock .

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