KR101873993B1

KR101873993B1 - Method and apparatus for predicting sample adaptive offset parameter

Info

Publication number: KR101873993B1
Application number: KR1020160153953A
Authority: KR
Inventors: 김성제; 김용환; 정진우
Original assignee: 전자부품연구원
Priority date: 2016-11-18
Filing date: 2016-11-18
Publication date: 2018-07-05
Also published as: WO2018092982A2; KR20180056447A; WO2018092982A3

Abstract

The present invention relates to a method and apparatus for adaptive sample offset parameter prediction in a video encoder, and more particularly to a method and apparatus for predicting adaptive sample offset parameters by determining an optimum mode using SAO type information of an already selected peripheral CTU, , And if necessary, compensation processing is performed to improve the adaptive sample offset parameter determination speed and finally to maintain the coding efficiency.

Description

[0001] METHOD AND APPARATUS FOR PREDICTING SAMPLE ADAPTIVE OFFSET PARAMETER [0002]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to Adaptive Sample Offset (SAO) technology in a video encoder, and more particularly, to SAO technology, which is a filter technology employed in HEVC (High Efficiency Video Coding) And an apparatus therefor.

The contents described in this section merely provide background information on the present embodiment and do not constitute the prior art.

With the development of digital video technology and broadcasting technology, high definition and high definition video services such as HD (High Definition) and UHD (Ultra High Definition) are expanding and interest in next generation video technology is increasing.

As a result, ISO / IEC and ITU-T, which are leading video compression technology standards, have established High-Efficiency Video Coding (HEVC), a next-generation video compression technology standard that has superior compression performance compared to existing video compression technology standards.

HEVC has superior compression performance compared to the conventional video compression standard because it has excellent encoding tools and optimal mode decision method. Especially, compared with the previous standard H.265 / AVC, the HEVC achieves 30 to 50% see.

In particular, the HEVC is an in-loop filtering method. In addition to the conventional de-blocking filter, the HEVC is adaptive to compensate distortion between an original image and a restored image generated through an encoding process, Sample Adaptive Offset (SAO) technology.

SAO technology has subjective image quality improvement and excellent coding efficiency because it applies different offset to each sample. However, since a large amount of computation is required to apply different offset type to each coding tree unit (CTU), the conventional compression standard There is a problem that the computational complexity is high.

Specifically, HEVC defines Coding Tree Unit (CTU) without using MB (Macro Block), unlike existing video codec, and uses CU (Coding Unit), PU (Prediction Unit) , And a Transform Unit (TU).

The adaptive sample offset parameter consists of SAO mode, SAO type and SAO offset in individual CTU units.

There are two types of SAO type, EO (Edge Offset) and BO (Band Offset). In case of type EO, one can have one of 0 degree, 90 degree, 135 degree and 45 degree direction. There is only one type. Therefore, the total number of SAO types is 5, and there are 5 corresponding offsets for each type.

The SAO mode can be classified into three types, and is referred to as mode OFF, mode MERGE, and mode NEW in order to describe the conventional technology.

Mode OFF means that the SAO filter is not applied to the current CTU, and mode MERGE means that the SAO type and offset of one of the neighboring CTUs are reused in the current CTU. In this case, since the SAO type and offset of the current CTU need not be transmitted to the decoder, it has a great advantage in reducing the bit rate.

Mode NEW means to newly calculate the SAO type and offset suitable for the current CTU.

1 is a flow chart of a conventional adaptive sample offset parameter prediction method.

First, statistical information on five types of SAO types is extracted (S11), an offset is calculated for each type (S12), a rate-distortion cost (RD) is calculated (S13) (Step S14). At this time, the smaller the RD Cost value, the smaller the difference from the original. In this way, it is called mode NEW to newly calculate the SAO type and offset suitable for the current CTU.

The SAO parameter of any one of the neighboring CTUs for which the SAO type and the offset have already been determined among the neighbor CTUs for the current CTU is extracted and applied thereto is referred to as a mode MERGE (S15).

For example, since the SAO type and offset of the current CTU often have a type and an offset statistically the same as the CTU of the left or top of the current CTU, the RD Cost of the left CTU or the upper CTU is calculated, SAO type and offset of SAO type and offset, which are applied to the current CTU to minimize the difference from the original, are determined and applied to the mode MERGE.

SAO mode The optimum mode is determined as the mode having the SAO type and the offset to minimize the difference between NEW, MERGE, and OFF from the original (S16).

The conventional method as described above has a problem that the computation load is large because statistical information is extracted for all five SAO types and the offset is calculated and a plurality of RD cost comparisons are performed.

Korean Patent Publication No. 10-2013-0102603, published on September 17, 2013 (name: Apparatus and method of sample adaptive offset for video coding)

Accordingly, the present invention provides an adaptive sample offset parameter prediction method that increases the computation speed by deriving an optimal parameter using SAO parameter information of a neighboring CTU whose SAO type and offset have already been determined centering on a current CTU to be encoded, and And to provide a device for such use.

In addition, the present invention provides an adaptive sample offset parameter prediction method and a device therefor that can maximize the encoding efficiency while increasing the computation speed by performing a compensation process when the selected optimal mode satisfies a predetermined compensation condition do.

According to an aspect of the present invention, there is provided an apparatus for predicting an adaptive sample offset parameter, the apparatus comprising: a SAO type determining unit for determining a SAO type of at least one neighboring CTU selected from a plurality of neighboring CTUs for a current CTU A first mode derivation unit for calculating a first SAO parameter for the current CTU using statistical information on the current CTU; A second mode derivation unit for extracting a SAO parameter of one surrounding CTU among the neighboring CTUs for the current CTU with a second SAO parameter of the current CTU; And an optimal mode determination unit for selecting one of the SAO mode off, the first SAO parameter, and the second SAO parameter so that the difference between the restored image and the original image is minimized.

In the apparatus for predicting adaptive sample offset parameters according to the preferred embodiment of the present invention, the first mode derivation unit may select at least one neighboring CTU according to a predetermined priority among neighboring CTUs centering on the current CTU .

In this case, the first mode derivation unit may further consider the SAO type of the selected neighboring CTU, in addition to the SAO type that is selected most when the SAO parameter is determined in the previous frame.

If it is determined that the selection result of the optimum mode determination unit satisfies a predetermined compensation condition, the current SAO type is calculated based on the statistical information on the remaining SAO types excluding the SAO type used in calculating the first SAO parameter, And a control unit for controlling the first mode derivation unit to re-calculate the first SAO parameter of the CTU.

In this case, the controller may be configured to reselect the SAO parameter that minimizes the difference between the reconstructed image and the original image among the selected result previously selected by the optimal mode determination unit and the recalculated first SAO parameter, Can be controlled.

At this time, the compensation condition may be set such that the selection result of the optimum mode determination unit is the SAO mode off.

At this time, the compensation condition may be set to include at least one of a Rate-Distortion Cost (RD Cost), a Temporal Layer, and a Quantized Coefficient.

According to another aspect of the present invention, there is provided a method of predicting adaptive sample offset parameters, the method comprising the steps of: (a) calculating statistical information on a SAO type of at least one neighboring CTU selected from a plurality of neighbor CTUs for a current CTU to be encoded A first mode derivation step of calculating a first SAO parameter for the current CTU using the first SAO parameter; A second mode derivation step of extracting, as a second SAO parameter of the current CTU, an SAO parameter of one surrounding CTU of the neighboring CTUs for the current CTU; And an optimal mode determining step of selecting one of the SAO mode off, the first SAO parameter, and the second SAO parameter so that the difference between the restored image and the original image is minimized.

In the adaptive sample offset parameter prediction method according to the preferred embodiment of the present invention, the first mode derivation step may include selecting at least one neighboring CTU based on a predetermined priority among neighboring CTUs centering on the current CTU In addition to the SAO type of the selected neighboring CTU, the most-selected SAO type may be further considered when determining the SAO parameter in the previous frame.

Determining whether the selection result of the optimal mode determination step satisfies a predetermined compensation condition; Re-calculating the first SAO parameter of the current CTU using the statistical information on the remaining SAO types except for the SAO type used in calculating the first SAO parameter when the compensation condition is satisfied; Reselecting the SAO parameter that minimizes the difference between the reconstructed image and the original image among the selected selection result of the optimal mode determination step and the recalculated first SAO parameter.

According to an aspect of the present invention, there is provided a computer-readable recording medium having recorded thereon a computer program for executing an adaptive sample offset parameter prediction method.

According to an aspect of the present invention, there is provided a computer program for implementing the method of predicting adaptive sample offset parameters, the computer program being stored in a computer readable recording medium.

The present invention determines the optimum SAO parameter by using the SAO type information of the determined neighboring CTU, rather than calculating all the offsets for each type in the video encoder, thereby increasing the computation efficiency.

Further, after determining a mode having an optimum parameter at high speed, a compensation process is performed if necessary, so that coding efficiency can be maintained.

1 is a flow chart of a conventional adaptive sample offset parameter prediction method.
2 is a block diagram of an apparatus for providing an adaptive sample offset parameter prediction method according to an embodiment of the present invention.
3 is an overall flowchart of an adaptive sample offset parameter prediction method in accordance with an embodiment of the present invention.
4 is a specific flowchart of a method for calculating a first SAO parameter according to an embodiment of the present invention.
FIGS. 5A and 5B are diagrams illustrating a neighbor CTU for a current CTU according to an embodiment of the present invention.
6 is a flowchart illustrating a compensation process including a compensation condition according to an embodiment of the present invention.
7 is a flowchart illustrating a compensation process including a compensation condition according to another embodiment of the present invention.
8 is a flowchart illustrating a compensation process according to an embodiment of the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS For a more complete understanding of the nature and advantages of the present invention, reference should be made to the following detailed description taken in conjunction with the accompanying drawings, in which:

In the following description and the accompanying drawings, detailed description of well-known functions or constructions that may obscure the subject matter of the present invention will be omitted. It should be noted that the same constituent elements are denoted by the same reference numerals as possible throughout the drawings.

The terms and words used in the present specification and claims should not be construed to be limited to ordinary or dictionary meanings and the inventor is not limited to the concept of terminology for describing his or her invention in the best way. It should be interpreted as meaning and concept consistent with the technical idea of the present invention.

Therefore, the embodiments described in the present specification and the configurations shown in the drawings are merely the most preferred embodiments of the present invention, and not all of the technical ideas of the present invention are described. Therefore, It is to be understood that equivalents and modifications are possible.

Also, terms including ordinal numbers such as first, second, etc. are used to describe various elements, and are used only for the purpose of distinguishing one element from another, Not used. For example, without departing from the scope of the present invention, the second component may be referred to as a first component, and similarly, the first component may also be referred to as a second component.

In addition, when referring to an element as being "connected" or "connected" to another element, it means that it can be connected or connected logically or physically. In other words, it is to be understood that although an element may be directly connected or connected to another element, there may be other elements in between, or indirectly connected or connected.

Also, the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise.

It is also to be understood that the terms such as " comprises "or" having ", as used herein, are intended to specify the presence of stated features, integers, And does not preclude the presence or addition of other features, numbers, steps, elements, components, or combinations thereof.

Also, the terms "part," "module," and the like, which are described in the specification, refer to a unit for processing at least one function or operation, and may be implemented by hardware or software or a combination of hardware and software.

It will also be understood by those skilled in the art that in the context of describing the invention (particularly in the context of the following claims), the terms " a or an, ""Quot; or " include ", unless the context clearly dictates otherwise.

In this specification, the first mode corresponds to the mode NEW and the SAO type and the offset, which are SAO parameters for the current CTU, are newly calculated. In the second mode, the SAO parameter of the surrounding CTU for the current CTU is extracted, And corresponds to the mode MERGE, and the SAO mode off corresponds to the mode OFF by not applying the SAO filter to the current CTU.

Now, an adaptive sample offset parameter prediction method and an apparatus therefor according to an embodiment of the present invention will be described in detail with reference to the drawings.

2 is a block diagram of an apparatus for providing an adaptive sample offset parameter prediction method according to an embodiment of the present invention.

Referring to FIG. 2, an apparatus 100 for providing an adaptive sample offset parameter prediction method according to an embodiment of the present invention includes a first mode derivation unit 110, a second mode derivation unit 120, The first mode derivation unit 110 may include a neighboring CTU determination module 112 and a neighboring CTU determination module 112. The first mode derivation unit 110 may include a neighboring CTU determination module 112,

The first mode derivation unit 110 newly calculates the SAO type and the offset suitable for the current CTU as the first SAO parameter.

The first mode derivation unit 110 does not calculate all of the offsets for the four EO types and one BO type but uses the SAO parameter information of the surrounding CTU for the current CTU to be encoded.

The neighboring CTUs are the CTUs whose SAO type and offset have been determined by performing SAO filtering, and mean one or more CTUs neighboring the current CTU.

The method of selecting the neighboring CTUs in the neighboring CTU determination module 112 for calculating the first SAO parameter is based on a predetermined priority, and a detailed method will be described later.

The first SAO parameter for the current CTU is calculated using the statistical information on the SAO type of the selected neighboring CTU. First, statistical information on the SAO type of the surrounding CTU is extracted, and the SAO offset is calculated, And determines the optimal SAO type and offset as a first SAO parameter by comparing RD Cost.

The second mode derivation unit 120 extracts the SAO parameter of one neighboring CTU among the neighbor CTUs for the current CTU as the second SAO parameter of the current CTU.

For example, since the SAO type and offset of the current CTU are often statistically the same type and offset as the CTU located at the left or top of the current CTU spatially, the RD cost of the left CTU or the upper CTU The SAO type and the offset that allow the difference from the original to be applied to the current CTU to be the minimum among the SAO type and offset of the left or upper CTU can be extracted as the second SAO parameter.

The optimal mode determination unit 130 determines whether the SAO mode does not apply the current SAO filter to the current CTU and when the SAO mode is applied to the current CTU among the calculated first SAO parameter and the extracted second SAO parameter, Choose to minimize the difference. When the SAO mode is selected, the optimum mode is the SAO mode off which does not apply the SAO filter. When the first SAO parameter is selected, the first mode in which the first SAO parameter is applied to the current CTU is the optimal mode When the second SAO parameter is selected, the second mode in which the second SAO parameter is applied to the current CTU is the optimal mode.

On the other hand, the first mode derivation unit 110 may consider the most-selected SAO type at the time of determining the SAO parameter in the previous frame, in addition to the SAO type of the selected peripheral CTU at the time of calculating the first SAO parameter.

For example, if two surrounding CTUs are selected, and each type is 0 degrees and 90 degrees for type EO, and the SAO type most frequently selected in the previous frame is type BO, the type EO It calculates the offset for three SAO types up to type BO in addition to 0 degrees and 90 degrees.

The apparatus 100 for providing an adaptive sample offset parameter prediction method may further include a control unit 140. The control unit 140 may be configured such that the optimal mode decision unit 130 actually selects an optimum mode It is determined whether the compensation condition stored in the storage unit 150 is satisfied. If the compensation condition is satisfied, the statistical information on the remaining SAO types excluding the SAO type used in calculating the first SAO parameter And controls the first mode derivation unit 110 to recalculate the first SAO parameter of the current CTU.

For example, if the first SAO parameter has been calculated by using 0 degree, 90 degree, and type BO of type EO in the first mode derivation unit 110, the remaining types 135 degrees and 45 degrees are used And recalculates the first SAO parameter.

In addition, the controller 140 may optimize the SAO parameter for reselecting the SAO parameter that minimizes the difference between the reconstructed image and the original image among the selected result selected first by the optimal mode determination unit 130 and the re- And controls the mode determination unit 130.

The storage unit 150 is for storing data and may store the method of configuring the neighboring CTUs and priorities for selecting the neighboring CTUs in the neighboring CTU determination module 112.

In addition, the storage unit 150 may store a compensation condition for determining whether a result selected by the optimal mode determination unit requires a compensation process.

The compensation condition according to an embodiment of the present invention is a case where the result selected by the optimum mode determination unit 130 is the SAO mode off.

The mode off is to not apply the SAO filter to the current CTU. If the filter is not applied, it is determined that there is no optimum type and offset among the first SAO parameter and the second SAO parameter. To determine a more suitable type and an offset thereto.

The compensation condition according to another embodiment of the present invention may take into consideration at least one of RD Cost, Temporal Layer, presence or absence of non-zero quantized coefficient in the current CTU.

If the RD Cost has a value smaller than 0, the image quality of the restored image is good. Therefore, if the RD Cost of the SAO type determined as the optimal mode is a value smaller than 0, there is no need to perform the compensation process.

In addition, Temporal Layer means that layers are layered by Layer 0, Layer 1, Layer 2, etc., while encoding on a frame basis according to time axis, and Layer 0 means the best coded layer.

Non-Zero Quantized Coefficient means that at least one Transform Unit (TU) has non-zero Quantized Coefficient when Transform and Quantization are applied to current CTU. If all subblocks in the CTU have a value of 0, it means All-Zero Condition, which means it is almost the same as the original image.

On the basis of this, the compensation condition according to another embodiment of the present invention is that when the RD Cost is equal to or greater than 0, Temporal Layer 0 (TL 0), or RD Cost is greater than or equal to 0 and Non-Zero Quantized In the case where the above condition is satisfied, the controller 140 controls the first mode deriving unit 110 and the second mode deriving unit 110 so that the compensation process can be performed. And controls the mode determination unit 130.

The adaptive sample offset parameter prediction method provided by the apparatus 100 for predicting the adaptive sample offset parameter according to the above-described embodiment of the present invention will be described in more detail with reference to FIG. 3 to FIG.

FIG. 3 is a general flowchart of an adaptive sample offset parameter prediction method according to an embodiment of the present invention, FIG. 4 is a specific flowchart of a method of calculating a first SAO parameter according to an embodiment of the present invention, And 5b is a diagram illustrating a peripheral CTU for a current CTU according to an embodiment of the present invention.

Referring to FIGS. 3 to 5B, a SAO type and an offset first SAO parameter suitable for the current CTU are newly calculated (S310). In calculating the first SAO parameter, the surrounding CTU is selected (S311) as shown in FIG. 4, and the SAO type of the selected peripheral CTU is used instead of calculating the offset for all the SAO types to improve the computing efficiency.

5A, the neighboring CTUs of the Cur (502), which are the current CTUs to be encoded, can be constructed. The neighboring CTUs 500 include four CTUs at the upper left, upper right, upper left, And nine CTUs 510 of Col_0 to Col_8. Where Col_4 512 is the co-located CTU corresponding to Cur (502), which is the current CTU.

In calculating the first SAO parameter, as many peripheral CTUs are used, the computational complexity is high as in the conventional method. Therefore, in the embodiment of the present invention, the number of peripheral CTUs can be appropriately selected according to a predetermined priority.

Since the offset of the left, top, and Col_4 (512) CTUs is statistically similar to the offset of the current CTU, the priorities can be configured as shown in FIG. 5B. You can choose.

Statistical information on the SAO type of the selected peripheral CTU is extracted (S312), SAO offset is calculated according to each type (S313), and RD Cost is calculated (S314). Since the image quality is better as the RD Cost value is smaller, the optimum SAO type and offset are determined through comparison of RD Cost (S315).

In another embodiment of the present invention, in addition to the SAO type of the peripheral CTU selected in S311, the most frequently selected SAO type in the previous frame may be further considered in S312 to S314.

After the first SAO parameter is calculated (S310), the second SAO parameter is extracted (S320). The second mode is referred to as a second mode, and the second mode uses the SAO type and offset of the CTUs on the left and top sides of the current CTU to calculate the RD Cost, And extracts the optimal SAO type and offset from the top with the second SAO parameter.

When the SAO parameter is applied to the current CTU among the first SAO parameter, the second SAO parameter, and the SAO mode off in which the SAO filter is not applied, the optimal mode is selected such that the difference between the restored image and the original image is minimized ).

Since the selected optimum mode may not be the optimum mode, the compensation condition determination unit 140 determines whether to perform the compensation process by comparing the compensation condition with the compensation condition previously stored (S340, S350)

FIG. 6 is a flowchart illustrating a compensation process including a compensation condition according to an exemplary embodiment of the present invention. FIG. 7 is a flowchart illustrating a compensation process including a compensation condition according to another exemplary embodiment of the present invention. 6 is a flowchart illustrating a compensation process according to an embodiment of the present invention.

Referring to FIG. 6, in operation S342, it is determined whether the selected optimal mode is the SAO mode off state (S342) after selecting the optimum mode in S330 in an exemplary embodiment of the present invention (Step S350). If the optimal mode is selected as the SAO mode off as described above, it is determined that there is no optimum offset in the first mode or the second mode in which the first SAO parameter or the second SAO parameter is applied. Therefore, This is because the encoding efficiency can be maintained by determining the offset.

Referring to FIG. 7, in step S334, the presence or absence of RD Cost, Temporal Layer, and Non-Zero Quantization Coefficient is considered as a condition after the optimal mode determination (S330).

More specifically, it is determined whether RD Cost is equal to or greater than 0 and Temporal Layer 0, or RD Cost is greater than or equal to 0, Temporal Layer 1 or 2, and Non-Zero Quantization Coefficient.

Referring to FIG. 8, when the compensation condition according to the present invention according to S342 or S344 is satisfied, the compensation process is performed. In calculating the first calculated SAO parameter, the SAO type The new first SAO parameter is re-calculated in the same manner (S352). That is, statistical information is extracted for the remaining SAO types to calculate an offset, and a new first SAO parameter is re-calculated through comparison of RD Cost.

The SAO mode having the SAO type and the offset to minimize the difference between the reconstructed image and the original image is applied to the CTU among the newly calculated first SAO parameter and the previously selected optimal mode, (S354).

The method steps herein may be performed by one or more programmable processors executing a computer program to perform functions by operating on input data and generating an output. The method steps may also be performed by special purpose logic circuitry, e.g., a field programmable gate-off (FPGA) or application-specific integrated circuit (ASIC), and the devices may be implemented as such.

Processors suitable for processing a computer program include, by way of example, both general purpose and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor will receive instructions and data from a read-only memory or a random access memory or both. The elements of a computer may include at least one processor for executing instructions and one or more memory devices for storing instructions and data.

In general, a computer may include one or more mass storage devices for storing data, for example, magnetic-optical disks, or optical disks, or may receive data from, transmit data to, Respectively.

Information carriers suitable for embodying computer program instructions and data include, for example, semiconductor memory devices, for example, magnetic media such as hard disks, floppy disks, and magnetic tape, Compact Disk Read Only Memory (CD ROM) An optical recording medium such as a DVD (Digital Video Disk), a magneto-optical medium such as a floppy disk, a ROM (Read Only Memory), a RAM Access Memory), flash memory, EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), and the like.

The processor and memory may be supplemented or included by special purpose logic circuitry.

While the specification contains a number of specific implementation details, it should be understood that they are not to be construed as limitations on the scope of any invention or claim, but rather on the description of features that may be specific to a particular embodiment of a particular invention Should be understood.

Certain features described herein in the context of separate embodiments may be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented in multiple embodiments, either individually or in any suitable subcombination.

Further, although the features may operate in a particular combination and may be initially described as so claimed, one or more features from the claimed combination may in some cases be excluded from the combination, Or a variant of a subcombination.

Likewise, although the operations are depicted in the drawings in a particular order, it should be understood that such operations must be performed in that particular order or sequential order shown to obtain the desired result, or that all depicted operations should be performed.

In certain cases, multitasking and parallel processing may be advantageous. Also, the separation of the various system components of the above-described embodiments should not be understood as requiring such separation in all embodiments, and the described program components and systems will generally be integrated together into a single software product or packaged into multiple software products It should be understood.

Certain embodiments of the subject matter described herein have been described. Other embodiments are within the scope of the following claims.

For example, the operations recited in the claims may be performed in a different order and still achieve desirable results. By way of example, the process illustrated in the accompanying drawings does not necessarily require that particular illustrated or sequential order to obtain the desired results.

The description sets forth the best mode of the invention, and is provided to illustrate the invention and to enable those skilled in the art to make and use the invention. The embodiments of the present invention described in the present specification and drawings are merely given specific examples for the purpose of understanding and are not intended to limit the scope of the present invention. It will be apparent to those skilled in the art that other modifications based on the technical idea of the present invention are possible in addition to the embodiments disclosed herein.

The present invention relates to an adaptive sample offset parameter prediction method and apparatus therefor, and uses an SAO type of a surrounding CTU for a current CTU to be encoded to determine an optimal mode for minimizing a difference from an original at a high speed.

In addition, a more suitable SAO type and offset can be determined by performing a compensation process if necessary.

Therefore, it is possible to increase the operation speed and improve the picture quality while maintaining the coding efficiency.

In addition, the present invention has a possibility of commercial use or business, and is industrially applicable because it is practically possible to carry out clearly.

100: adaptive sample offset parameter prediction device
110: first mode derivation unit
112: peripheral CTU determination module
120: second mode derivation unit
130: Optimum mode decision unit
140:
150:

Claims

An apparatus for predicting an adaptive sample offset parameter for a video encoder that performs encoding by dividing a frame into CTU (Coding Tree Unit) units,
A first mode for calculating a first SAO parameter for the current CTU using statistical information on a SAO type of one or more neighboring CTUs neighboring the current CTU to be encoded and selected from a plurality of neighboring CTUs whose SAO type and offset are determined; A derivation unit;
A second mode derivation unit for extracting a SAO parameter determined for a specific peripheral CTU neighboring the current CTU and selected among the plurality of neighboring CTUs whose SAO type and offset are determined to be the second SAO parameter of the current CTU; And
An optimal mode determining unit that selects one of the SAO mode off, the first SAO parameter, and the second SAO parameter as the SAO parameter of the current CTU so that the difference between the restored image and the original image is minimized;
Wherein the adaptive sample offset parameter estimator comprises:

The apparatus of claim 1, wherein the first mode derivation unit
And selects at least one neighboring CTU according to a predetermined priority among neighboring CTUs centering on the current CTU.

3. The apparatus of claim 2, wherein the first mode derivation unit
Wherein the first SAO parameter is calculated by taking into account the SAO type of the selected neighboring CTU and the most frequently selected SAO type in determining the SAO parameter in the previous frame of the frame including the current CTU. / RTI >

The method according to claim 1,
Determining whether the selection result of the best mode determining unit satisfies a predetermined compensation condition, and if the selection result of the best mode determining unit satisfies the predetermined SAO type, A control unit for controlling the first mode deriving unit to re-calculate the first SAO parameter;
Further comprising an adaptive sample offset parameter estimator.

5. The apparatus of claim 4,
The optimum mode determination unit is configured to reselect the SAO parameter that minimizes the difference between the reconstructed image and the original image among the selected result selected first by the optimal mode determination unit and the recalculated first SAO parameter The adaptive sample offset parameter estimating apparatus comprising:

5. The method according to claim 4,
And the selection result of the best mode decision unit is the SAO mode off.

5. The method according to claim 4,
RD, a rate-distortion cost, a temporal layer, and a quantized coefficient.

1. An adaptive sample offset parameter prediction method for a video encoder that performs encoding by dividing a frame into CTU (Coding Tree Unit) units,
A first mode for calculating a first SAO parameter for the current CTU using statistical information on a SAO type of one or more neighboring CTUs neighboring the current CTU to be encoded and selected from a plurality of neighboring CTUs whose SAO type and offset are determined; A derivation step;
A second mode derivation step of extracting a SAO parameter of a selected one of a plurality of neighboring CTUs adjacent to the current CTU and whose SAO type and offset are determined as a second SAO parameter for the current CTU;
Determining an SAO mode off, a first SAO parameter, and a second SAO parameter as SAO parameters of the current CTU so that the difference between the restored image and the original image is minimized;
Wherein the adaptive sample offset parameter prediction method comprises:

9. The method of claim 8,
And selecting at least one neighboring CTU according to a predetermined priority among neighboring CTUs centering on the current CTU,
Further comprising, in addition to the SAO type of the selected neighboring CTU, the most-selected SAO type when determining SAO parameters in a previous frame.

9. The method of claim 8,
Determining whether the selection result of the optimal mode determination step satisfies a predetermined compensation condition;
Re-calculating the first SAO parameter of the current CTU using the statistical information on the remaining SAO types except for the SAO type used in calculating the first SAO parameter when the compensation condition is satisfied;
Reselecting the SAO parameter that minimizes the difference between the reconstructed image and the original image among the selected selection result of the optimal mode determination step and the recalculated first SAO parameter;
&Lt; / RTI > further comprising: estimating an adaptive sample offset parameter.

11. The method according to claim 10,
And the selection result of the optimal mode determination step is SAO mode off.

11. The method according to claim 10,
RD Cost (Rate-Distortion Cost), Temporal Layer, Quantized Coefficient, and the like.