KR20180095777A - Method and apparatus for parallel entropy encoding/decoding - Google Patents

Abstract

According to the present invention, a method for entropy encoding comprises the steps of: drawing scheduling information from a header of a bit stream received from an encoder; rearranging a partial bit stream constituting the received bit stream in a de-binarization order using the drawn scheduling information; drawing a bin corresponding to the bit stream based on the rearranged partial bit stream; and obtaining a syntax element by performing de-binarization to the drawn bin. According to the present invention, efficiency of image encoding/decoding may be improved.

Description

TECHNICAL FIELD [0001] The present invention relates to a parallel entropy encoding /

The present invention relates to image processing, and more particularly, to an entropy encoding / decoding method and apparatus.

Recently, broadcasting service having high definition (HD) resolution has been expanded not only in domestic but also in the world, so that many users are accustomed to high definition and high definition video, and accordingly, many organizations are spurring development for next generation video equipment. In addition, with the increase of interest in UHD (Ultra High Definition) having resolution more than 4 times of HDTV in addition to HDTV, a compression technique for a higher resolution and a higher image quality is required.

An inter prediction technique for predicting pixel values included in the current picture from temporally preceding and / or following pictures for image compression, prediction of pixel values included in the current picture using pixel information in the current picture An intra prediction technique, an entropy coding technique in which a short code is assigned to a symbol having a high appearance frequency and a long code is assigned to a symbol having a low appearance frequency.

SUMMARY OF THE INVENTION The present invention provides an image encoding method and apparatus capable of improving image encoding / decoding efficiency.

Another aspect of the present invention is to provide an image decoding method and apparatus capable of improving image encoding / decoding efficiency.

It is another object of the present invention to provide an entropy encoding method and apparatus capable of improving image encoding / decoding efficiency.

Another object of the present invention is to provide an entropy decoding method and apparatus capable of improving image encoding / decoding efficiency.

1. An embodiment of the present invention is an entropy decoding method. The method includes deriving scheduling information from a header of a bitstream received from an encoder, de-binarizing a partial bitstream constituting the received bitstream using the derived scheduling information, Deriving a bin corresponding to the bitstream based on the rearranged partial bitstream and dequantizing the derived bin to obtain a syntax element, Wherein the scheduling information includes information on the position of each of the partial bitstreams constituting the received bitstream and information on an inverse binarization order of the partial bitstream.

2. The method of claim 1, wherein the entire probability interval for the LPB (Least Probable Bin) probability of the bin is classified into a plurality of probability intervals each having a representative probability, the partial bitstream is composed of at least one code word, The codewords constituting the partial bitstream may correspond to the same representative probability.

3. The method of claim 3, wherein the bin derivation comprises deriving codeword length information from a header of the received bitstream and deriving a bin corresponding to the bitstream based on the derived codeword length information And the codeword length information may be information on a minimum length and a maximum length of a codeword with respect to a representative probability of each of the plurality of probability intervals.

4. The method of claim 3, wherein the bin derivation step comprises the steps of: determining a codeword-to-be mappings table for each representative probability of the plurality of probability intervals using the derived codeword length information; - deriving a bin corresponding to the bitstream using an empty mapping table.

5. Another embodiment of the present invention is an entropy decoding apparatus. The apparatus derives scheduling information from a header of a bit stream received from an encoder and performs a de-binarization sequence of the partial bit streams constituting the received bit stream using the derived scheduling information A bin decoder for deriving a bin corresponding to the bitstream based on the rearranged partial bitstream, and a binarizer for binarizing the derived bin to generate a syntax element wherein the scheduling information includes at least one of information on the position of each of the partial bitstreams constituting the received bitstream and information on the position of each bitstream in the inverse binarization sequence of the partial bitstream. And the like.

6. The method of claim 5, wherein the entire probability interval for the LPB (Least Probable Bin) probability of the bin is classified into a plurality of probability intervals each having a representative probability, the partial bitstream is composed of at least one code word, The codewords constituting the partial bitstream may correspond to the same representative probability.

7. The apparatus of claim 6, further comprising a codeword length calculator for deriving codeword length information from the header of the received bitstream, wherein the codeword length decoder comprises: And the codeword length information may be information on a minimum length and a maximum length of a codeword with respect to a representative probability of each of the plurality of probability intervals.

8. The apparatus of claim 7, further comprising a mapping table determiner for determining a code word-to-be mappings table for the representative probabilities of each of the plurality of probability intervals using the derived codeword length information, The decoder may derive a bin corresponding to the bitstream using the determined codeword-to-bean mapping table.

9. Another embodiment of the present invention is a video decoding method. The method includes deriving scheduling information from a header of a bitstream received from an encoder, de-binarizing a partial bitstream constituting the received bitstream using the derived scheduling information, Deriving a bin corresponding to the bitstream based on the rearranged partial bitstream, inverse binarizing the derived bin to obtain a syntax element, And generating a reconstructed image using the acquired syntax elements, wherein the scheduling information includes information on positions of partial bitstreams constituting the received bitstream and information on positions of the partial bitstreams inverse- As shown in FIG.

10. The method of claim 9, wherein the entire probability interval for the LPB (Least Probable Bin) probability of the bin is classified into a plurality of probability intervals each having a representative probability, the partial bitstream is composed of at least one code word, The codewords constituting the partial bitstream may correspond to the same representative probability.

11. The method of claim 10, wherein the bin derivation comprises deriving codeword length information from a header of the received bitstream and deriving a bin corresponding to the bitstream based on the derived codeword length information And the codeword length information may be information on a minimum length and a maximum length of a codeword with respect to a representative probability of each of the plurality of probability intervals.

12. The method of claim 11, wherein the bin derivation step comprises the steps of: determining a codeword-to-be mappings table for each representative probability of the plurality of probability intervals using the derived codeword length information; - deriving a bin corresponding to the bitstream using an empty mapping table.

According to the image encoding method of the present invention, image encoding / decoding efficiency can be improved.

According to the image decoding method of the present invention, image encoding / decoding efficiency can be improved.

According to the entropy encoding method of the present invention, image encoding / decoding efficiency can be improved.

According to the entropy decoding method of the present invention, image encoding / decoding efficiency can be improved.

1 is a block diagram illustrating a configuration of an image encoding apparatus according to an embodiment of the present invention.
2 is a block diagram illustrating a configuration of an image decoding apparatus according to an embodiment of the present invention.
3 is a table schematically illustrating one embodiment of codeword length limitation in accordance with the present invention.
4 is a conceptual diagram schematically showing an embodiment of a scheduling method for a bitstream parsing process according to the present invention.
5 is a conceptual diagram schematically showing another embodiment of a scheduling method for a bitstream parsing process according to the present invention.
6 is a block diagram schematically showing an embodiment of a parallel entropy encoding apparatus according to the present invention.
7 is a block diagram schematically showing an embodiment of a parallel entropy decoding apparatus according to the present invention.
8 is a block diagram schematically showing another embodiment of the parallel entropy encoding apparatus according to the present invention.
9 is a block diagram schematically showing another embodiment of a parallel entropy decoding apparatus according to the present invention.
10 is a block diagram schematically showing another embodiment of a parallel entropy encoding apparatus according to the present invention.
11 is a block diagram schematically showing another embodiment of a parallel entropy decoding apparatus according to the present invention.
12 is a flowchart schematically showing an embodiment of a parallel entropy encoding method according to the present invention.
13 is a flowchart schematically illustrating an embodiment of a parallel entropy decoding method according to the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. In the following description of the embodiments of the present invention, a detailed description of known functions and configurations incorporated herein will be omitted when it may make the subject matter of the present disclosure rather unclear.

It is to be understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, . In addition, the description of "including" a specific configuration in the present invention does not exclude a configuration other than the configuration, and means that additional configurations can be included in the practice of the present invention or the technical scope of the present invention.

The terms first, second, etc. may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component.

In addition, the components shown in the embodiments of the present invention are shown independently to represent different characteristic functions, which does not mean that each component is composed of separate hardware or software constituent units. That is, each constituent unit is included in each constituent unit for convenience of explanation, and at least two constituent units of the constituent units may be combined to form one constituent unit, or one constituent unit may be divided into a plurality of constituent units to perform a function. The integrated embodiments and separate embodiments of the components are also included within the scope of the present invention, unless they depart from the essence of the present invention.

In addition, some of the components are not essential components to perform essential functions in the present invention, but may be optional components only to improve performance. The present invention can be implemented only with components essential for realizing the essence of the present invention, except for the components used for the performance improvement, and can be implemented by only including the essential components except the optional components used for performance improvement Are also included in the scope of the present invention.

1 is a block diagram illustrating a configuration of an image encoding apparatus according to an embodiment of the present invention.

1, the image encoding apparatus 100 includes a motion prediction unit 111, a motion compensation unit 112, an intra prediction unit 120, a switch 115, a subtractor 125, a transform unit 130, A quantization unit 140, an entropy encoding unit 150, an inverse quantization unit 160, an inverse transformation unit 170, an adder 175, a filter unit 180, and a reference picture buffer 190.

The image encoding apparatus 100 may encode an input image in an intra mode or an inter mode and output a bit stream. In the intra mode, the switch 115 is switched to the intra mode, and in the inter mode, the switch 115 can be switched to the inter mode. The image encoding apparatus 100 may generate a prediction block for an input block of an input image, and then may code a residual between the input block and the prediction block.

In the intra mode, the intra prediction unit 120 may generate a prediction block by performing spatial prediction using the pixel value of the already coded block around the current block.

In the inter mode, the motion predicting unit 111 can find a motion vector by searching an area of the reference picture stored in the reference picture buffer 190 that is best matched with the input block. The motion compensation unit 112 may generate a prediction block by performing motion compensation using a motion vector.

The subtractor 125 may generate a residual block by a difference between the input block and the generated prediction block. The transforming unit 130 may perform a transform on the residual block to output a transform coefficient. The quantization unit 140 may quantize the input transform coefficient according to the quantization parameter to output a quantized coefficient.

The entropy encoding unit 150 may output a bit stream by performing entropy encoding based on the values calculated by the quantization unit 140 or the encoding parameter values calculated in the encoding process.

When entropy encoding is applied, a small number of bits are allocated to a symbol having a high probability of occurrence, and a large number of bits are allocated to a symbol having a low probability of occurrence, thereby expressing symbols, The size of the column can be reduced. Therefore, the compression performance of the image encoding can be enhanced through the entropy encoding. The entropy encoding unit 150 may use an encoding method such as exponential golomb, context-adaptive variable length coding (CAVLC), and context-adaptive binary arithmetic coding (CABAC) for entropy encoding.

Since the image encoding apparatus according to the embodiment of FIG. 1 performs inter prediction encoding, that is, inter-view prediction encoding, the currently encoded image needs to be decoded and stored for use as a reference image. Accordingly, the quantized coefficients are inversely quantized in the inverse quantization unit 160 and inversely transformed in the inverse transformation unit 170. The inverse quantized and inverse transformed coefficients are added to the prediction block through the adder 175 and a reconstructed block is generated.

The restoration block passes through the filter unit 180 and the filter unit 180 applies at least one of a deblocking filter, a sample adaptive offset (SAO), and an adaptive loop filter (ALF) can do. The filter unit 180 may be referred to as an adaptive in-loop filter. The deblocking filter can remove block distortion occurring at the boundary between the blocks. The SAO may add a proper offset value to the pixel value to compensate for coding errors. ALF can perform filtering based on the comparison between the reconstructed image and the original image. The reconstructed block having passed through the filter unit 180 may be stored in the reference picture buffer 190.

2 is a block diagram illustrating a configuration of an image decoding apparatus according to an embodiment of the present invention.

2, the image decoding apparatus 200 includes an entropy decoding unit 210, an inverse quantization unit 220, an inverse transform unit 230, an intra prediction unit 240, a motion compensation unit 250, (255), a filter unit (260), and a reference picture buffer (270).

The video decoding apparatus 200 receives the bit stream output from the encoder and decodes the video stream into the intra mode or the inter mode, and outputs the reconstructed video, that is, the reconstructed video. In the intra mode, the switch is switched to the intra mode, and in the inter mode, the switch can be switched to the inter mode. The image decoding apparatus 200 may obtain a reconstructed residual block from the input bitstream, generate a prediction block, and add the reconstructed residual block and the prediction block to generate a reconstructed block, i.e., a reconstructed block .

The entropy decoding unit 210 may entropy-decode the input bitstream according to a probability distribution to generate symbols including a symbol of a quantized coefficient type. The entropy decoding method is similar to the entropy encoding method described above.

When the entropy decoding method is applied, a small number of bits are assigned to a symbol having a high probability of occurrence, and a large number of bits are assigned to a symbol having a low probability of occurrence, so that the size of a bit string for each symbol is Can be reduced. Therefore, the compression performance of the image decoding can be enhanced through the entropy decoding method.

The quantized coefficients are inversely quantized in the inverse quantization unit 220 and inversely transformed in the inverse transformation unit 230. The reconstructed residual block can be generated as a result of inverse quantization / inverse transformation of the quantized coefficients.

In the intra mode, the intraprediction unit 240 may generate a prediction block by performing spatial prediction using the pixel values of the already coded blocks around the current block. In the inter mode, the motion compensation unit 250 may generate a prediction block by performing motion compensation using a motion vector and a reference image stored in the reference picture buffer 270. [

The reconstructed residual block and the prediction block are added through the adder 255, and the added block can be passed through the filter unit 260. The filter unit 260 may apply at least one of a deblocking filter, SAO, and ALF to a restoration block or a restored picture. The filter unit 260 may output a reconstructed image, that is, a reconstructed image. The restored image is stored in the reference picture buffer 270 and can be used for inter prediction.

As described above with reference to FIGS. 1 and 2, the encoder and the decoder can perform entropy encoding and entropy decoding, respectively. When entropy encoding / decoding is applied, a small number of bits are allocated to a symbol having a high probability of occurrence, and a large number of bits are allocated to a symbol having a low probability of occurrence, thereby expressing a symbol, The size can be reduced. The methods used for entropy encoding / decoding may be exponential Gullum, CAVLC, CABAC, and the like.

For example, a table for performing entropy encoding / decoding such as a variable length coding (VLC) table may be stored in an encoder and a decoder, and an encoder and a decoder may perform entropy encoding / decoding using a stored variable length coding table. Can be performed.

The encoder and the decoder may derive a binarization method of the object symbol and a probability model of the object symbol / bin, and then perform entropy encoding / decoding using the derived binarization method or probability model have.

Here, binarization means that the value of a symbol is represented by a binary sequence (bin sequence / string). A bin is a binary value (0 or 1) when a symbol is represented as a binary sequence through binarization. The probability model means a predicted probability of a symbol / bin to be encoded / decoded that can be derived through a context information / context model. The context information / context model is information for determining the probability of a symbol / bin to be encoded / decoded.

More specifically, the CABAC entropy encoding method converts a non-binarized symbol into a bin, transforms the binarized symbol into a bin, and uses the encoding information of the surrounding and encoding target blocks or the symbol / And generate a bitstream by performing arithmetic encoding of the bin by predicting the probability of occurrence of the bin according to the determined context model.

That is, the encoder / decoder can effectively perform entropy encoding / decoding using the encoding / decoding information of a neighboring block and the occurrence probability of a bin encoded / decoded in a previous stage. Also, in the encoding step, the encoder can select the context model through the encoding information of the neighboring blocks, and update the occurrence probability information of the generated beacon according to the selected context model.

When a single encoder and / or a single decoder is used for a UHD class image having a size equal to or higher than the HD level, the amount of work required for a single processor may be very large and the image processing speed may be very slow. Therefore, a method of improving the coding efficiency through parallelization of the encoding and / or decoding process can be provided. For this, a parallelization method for processes such as motion compensation, interpolation, DCT (Discrete Cosine Transform), and quantization may be provided, and a parallelization method may be applied to the above entropy encoding / decoding process.

The parallel entropy encoding / decoding may be performed using a plurality of entropy encoders and / or a plurality of entropy decoders. Techniques used for parallel entropy encoding / decoding include Probability Interval Partitioning Entropy (PIPE), which maps and / or converts a variable length of a bin sequence to a variable length codeword, ) And variable length to variable length (V2V). The PIPE and V2V schemes can be applied to both a single entropy encoder / decoder and a parallel entropy encoder / decoder.

The probability of a bin in the parallel entropy encoding / decoding process can be divided according to the quantization interval. Each of the divided probability intervals may be allocated to a bin decoder corresponding to each probability interval on the encoder side and may be allocated to a bin decoder corresponding to each probability interval on the decoder side. Also, a representative probability value corresponding to each of the probability intervals may exist in each of the divided probability intervals. When a PIPE or V2V technique is used for parallel entropy encoding / decoding, a plurality of entropy encoders / decoders are coded using the LPB (Least Probable Bin) probability interval allocated thereto and the representative LPB probability value corresponding to the probability interval / Decryption can be performed. Here, LPB may mean a value of a bin that is less than the value of 0 and 1. Hereinafter, in the following embodiments, the probability interval may mean the LPB probability interval, and the representative probability may mean the representative LPB probability.

In the encoder, each parallelized entropy encoder codes a bean with a fixed representative probability, and the encoder can transmit a set of output codewords to a decoder in the form of a bitstream. For example, the encoder may binarize a to-be-encoded symbol and convert it into a bin, and predict and / or derive an LPB probability value for each of the to-be-encoded bins through a context modeler and / or a probability predictor. The encoder can derive a representative LPB probability for each of the probability interval and the probability interval for each bin using the LPB probability value predicted through the context modeler and / or the probability predictor. Each bin may be entropy encoded in a bin encoder that is assigned a corresponding probability interval. At this time, the bin sequence input to each empty encoder can be converted into a codeword by the codeword table. That is, the empty sequence input to each empty encoder can be output in the form of a code word through code word table mapping. The output codeword may be included in the bitstream and transmitted to the decoder in units of Network Abstraction Layer (NAL).

The bit stream transmitted to the decoder may be parsed by a decoder. In the parsing process, the decoder may map and / or convert variable-length codewords into a variable-length, empty sequence. At this time, in the comparison process for each bin, overhead may occur.

Also, the number of entropy encoders included in the encoder may be different from the number of entropy decoders included in the decoder. For example, when the encoded bitstream is transmitted to and decoded by the decoder, if the number of entropy decoders is less than the number of entropy decoders May be smaller than the number of encoders. In this case, for example, each entropy decoder may parse a bitstream corresponding to one representative probability and then parse a bitstream corresponding to another representative probability. Since each bin after parsing is decoded into a value of a meaningful syntax element through a de-binarization process, the parsing process described above can cause a delay in the inverse binarization step, It may have a great influence on the decoding speed.

To reduce the delay in the inverse binarization step, each entropy encoder included in the encoder may add information on the decodable position in the bitstream to the header of the bitstream, and information on the decodable position may be added to the header May be transmitted to the decoder. In this specification, the decodable position may indicate a point at which entropy decoding starts in the minimum unit bit stream and / or a point where entropy decoding ends. In addition, the minimum unit bitstream may indicate a minimum unit in which the entropy decoding is performed in the bitstream transmitted from the encoder to the decoder. For example, the minimum unit bitstream corresponds to one codeword . At this time, each of the entropy decoders can perform entropy decoding from the midpoint of the bitstream (for example, the start point of the minimum unit bitstream) rather than the beginning point of the entire bitstream. The decoder may perform scheduling for a bitstream parsing process in each entropy decoder using information on the decodable position included in the header of the bitstream. However, even when the information on the decodable position is used as described above, since the bin before the post-reverse binarization is performed can not be recognized as the value of the meaningful syntax element, a delay occurs in the inverse binarization step And the output of the entropy decoder may be delayed.

As described above, when a delay occurs in the parsing process and the inverse binarization process, the parallel entropy encoding / decoding rate can be reduced. Accordingly, there is a need for a parallel entropy encoding / decoding method capable of minimizing the delay caused in the parsing process and the inverse binarization process.

3 is a table schematically illustrating one embodiment of codeword length limitation in accordance with the present invention. Figure 3 shows the minimum and maximum lengths of codewords for each fixed-probability value of the LPB that can be representative of LPB probabilities.

When a codeword that is the output of an entropy encoder is generated, the length of the codeword may have a variable value. However, as described above, when a variable length codeword is converted and / or mapped to a variable length empty sequence in the decoder, a large amount of computation is required, so that an overhead may occur in the codeword parsing process. Thus, a predetermined fixed length codeword may be used, in which case the parsing rate of the decoder may be improved. However, when a predetermined fixed length codeword is used, a problem may occur that the coding efficiency is reduced.

Therefore, in order to reduce the overhead incurred in the parsing process, the length of the codeword can be limited to a minimum length or more and a maximum length or less. The minimum length and the maximum length of the codeword can be defined for each representative LPB probability of the parallel entropy encoder. That is, the minimum length and the maximum length of the codeword can be defined in consideration of the representative LPB probability value of each entropy encoder in the encoder.

For example, the encoder may include a codeword length calculator. The codeword length calculator can derive an optimal codeword length (minimum length and maximum length) considering coding efficiency for each of the fixed probability values that can be representative. At this time, each of the entropy encoders included in the encoder can generate a codeword having a length equal to or smaller than the minimum length and equal to or smaller than the maximum length according to the representative probability value corresponding thereto. Figure 3 shows an embodiment of the minimum length and maximum length of the derived codeword.

Referring to FIG. 3, for each fixed probability value, the maximum and minimum lengths of codewords can be derived. For example, if the fixed probability value is 0.5, the maximum length of the codeword may be 8, and the minimum length of the codeword may be 6. Further, when the fixed probability value is 0.005, the maximum length of the codeword may be 13, and the minimum length of the codeword may be 1.

Also, in the embodiment of FIG. 3, the higher the fixed probability value, the smaller the maximum length value of the codeword and the larger the minimum length value. Therefore, as the fixed probability value of the LPB is larger, the variance of the codeword length value is smaller and the variance of the codeword length value is larger as the fixed probability value of the LPB is smaller.

The minimum length and the maximum length of the code word derived for each of the fixed probability values are not limited to the above-described embodiments, and can be derived in various forms in some cases. Hereinafter, the information on the minimum length and maximum length of the codeword derived from the encoder is referred to as codeword length information.

The codeword length information derived from the encoder may be included in the header of the bitstream and transmitted to the decoder. At this time, the decoder can map or convert codewords into an empty sequence using the transmitted codeword length information, and the parallel entropy decoding speed can be improved.

4 is a conceptual diagram schematically showing an embodiment of a scheduling method for a bitstream parsing process according to the present invention.

FIG. 4 illustrates a scheduling method when the number of bin encoders included in an encoder is equal to the number of bin decoders included in a decoder. In the embodiment of FIG. 4, it is assumed that the number of empty encoders and the number of empty decoders are four, respectively.

Reference numeral 410 in FIG. 4 shows an embodiment of a bitstream output from the encoder and transmitted to the decoder. Each block (dotted line block) constituting the bitstream may represent a minimum unit bitstream. For example, each minimum unit bitstream may correspond to one code word. The number indicated in each min unit bitstream may indicate the order in which the inverse binarization is performed after parsing. In addition, each of 411, 413, 415, and 417 in FIG. 4 may represent a set of all minimum unit bit streams corresponding to the representative probability of one empty encoder. Hereinafter, a set of all minimum unit bit streams corresponding to one representative probability and / or one probability interval is referred to as a representative probability unit bit stream.

420 of FIG. 4 shows an embodiment of a method of allocating the bitstream of FIG. 410 to the cores of four empty decoders. Referring to 420 of FIG. 4, one representative probability unit bitstream may be allocated to a core of one bin decoder. Here, the core may mean a processor for performing an operation. At this time, each bin decoder can perform entropy decoding on the representative probability unit bit stream allocated thereto.

After parsing, each bean can be decoded into a value of a meaningful syntax element through an inverse binarization process. At this time, the parsing process of converting the bit stream into the empty sequence can be performed independently of the inverse binarization process. For example, the order in which the bitstreams are converted to the empty sequence and the order in which the inverse binarization is performed can be determined separately. Therefore, at 420 in FIG. 4, the parsing of the bin required in the inverse binarization step is delayed, and the inverse binarization process may be delayed. That is, the parsing process according to the embodiment 420 of FIG. 4 may cause a delay of the inverse binarization step, which may cause a delay of the entire entropy decoder. Accordingly, an entropy decoding method capable of reducing the delay caused in the inverse binarization process can be provided.

Reference numeral 430 in FIG. 4 shows another embodiment of a bit stream outputted from the encoder and transmitted to the decoder. Each block (dotted line block) constituting the bitstream may represent a minimum unit bitstream. For example, each minimum unit bitstream may correspond to one code word. The number indicated in each min unit bitstream may indicate the order in which the inverse binarization is performed after parsing. In addition, each of 433, 435, 437, and 439 in FIG. 4 may represent a representative probability unit bit stream.

In addition, the bitstream header 431 of FIG. 4 may include scheduling information for scheduling of the bitstream parsing process. Here, the scheduling may refer to a process of rearranging the bit streams in consideration of the inverse binarization order of the syntax elements of the symbols. Once the scheduling is performed, the reordered bitstream can be assigned to an empty decoder. A specific embodiment of the scheduling information will be described later.

440 shows an embodiment of a method of allocating the bitstream of FIG. 430 to the cores of four empty decoders.

Referring to 440 of FIG. 4, one representative probability unit bitstream may be classified and / or divided into a plurality of partial bitstreams. Here, the partial bitstream may represent an entropy decoding unit determined by an encoder for bitstream reordering, and one partial bitstream may include one or a plurality of minimum unit bitstreams. When the representative probability unit bitstream is divided into partial bitstreams, each entropy decoder is not a starting point of the entirety of the representative probability unit bitstream, but is located at the midpoint of the bitstream (e.g., the starting point of the partial bitstream) You can start parsing.

The decoder may determine a bitstream to be allocated to each bin decoder by rearranging the partial bitstreams so that binaries required for priority in the inverse binarization process can be parsed first considering the inverse binarization order of the syntax elements of the symbols. In this case, the decoder may allocate a bitstream so that a plurality of binarizers may have similar workloads in consideration of the number of empty encoders.

The point at which the representative probability unit bit stream is divided and / or classified into the partial bit stream can be determined by the encoder, and the priority of parsing for each representative probability bit stream and / or each partial bit stream can also be determined in the encoder have. In the determination process, the encoder can determine the partial bit stream and the priority in consideration of the inverse binarization order of the syntax elements of the symbol.

Hereinafter, the information on the point where the representative probability unit bit stream is divided and / or classified into the partial bit stream is referred to as partial bit stream information, and information on each representative probability unit bit stream and / Information on the priority of parsing is called priority information. The above-described scheduling information may include the partial bitstream information and the priority information, and may include the additional information if there is additional information required for scheduling.

Once the scheduling information is determined, the entropy encoder may add the determined scheduling information to the header 431 of the bitstream and transmit it to the decoder. Based on the transmitted scheduling information, the decoder can recognize a high-priority representative probability unit bitstream and / or a high-priority partial bitstream, and perform parsing on a partial bitstream basis. The decoder can perform scheduling for the bitstream parsing process based on the scheduling information, thereby minimizing the delay generated in the inverse binarization step.

According to the above-described method, smooth job distribution can be performed between a plurality of empty decoders included in the decoder, and delay in the inverse binarization step can be minimized. Therefore, the output delay in the parallel entropy decoder can be minimized, and the process of performing entropy decoding can be speeded up.

5 is a conceptual diagram schematically showing another embodiment of a scheduling method for a bitstream parsing process according to the present invention.

FIG. 5 illustrates a scheduling method when the number of bin decoders included in the decoder is smaller than the number of bin encoders included in the encoder. In the embodiment of FIG. 5, it is assumed that the number of empty encoders is four and the number of empty decoders is three.

Reference numeral 510 in FIG. 5 shows an embodiment of a bit stream output from the encoder and transmitted to the decoder. Each block (dotted line block) constituting the bitstream may represent a minimum unit bitstream. For example, each minimum unit bitstream may correspond to one code word. The number indicated in each min unit bitstream may indicate the order in which the inverse binarization is performed after parsing. Each of 511, 513, 515, and 517 in FIG. 5 may represent a representative probability unit bit stream. 5, a total of four representative probability unit bit streams may exist.

520 of FIG. 5 shows an embodiment of a method of allocating the bitstream of FIG. 510 to the core of three empty decoders. Referring to 520 of FIG. 5, one representative probability unit bitstream may be allocated to a core of one bin decoder. At this time, each bin decoder can perform entropy decoding on the representative probability unit bit stream allocated thereto.

In 520 of FIG. 5, since the number of empty decoders is three, when starting parsing, one representative probability unit bit stream may be allocated to each of three empty decoders. At this time, the representative probability unit bit stream that is not allocated to the bin decoder may be parsed after at least one of the three representative probability unit bit streams allocated to the bin decoder is all parsed. In this case, a bin having a high inverse binarization priority may be parsed later than a bin having a low inverse binarization priority, and a delay may occur in the inverse binarization process. That is, the parsing process according to the embodiment 520 of FIG. 5 may cause a delay of the inverse binarization step, which may cause a delay of the entire entropy decoder. Accordingly, an entropy decoding method capable of reducing the delay caused in the inverse binarization process can be provided.

Reference numeral 530 in FIG. 5 shows another embodiment of the bit stream that is output from the encoder and transmitted to the decoder. Each block (dotted line block) constituting the bitstream may represent a minimum unit bitstream. For example, each minimum unit bitstream may correspond to one code word. The number indicated in each min unit bitstream may indicate the order in which the inverse binarization is performed after parsing. Each of 533, 535, 537, and 539 in FIG. 5 may represent a representative probability unit bit stream.

In addition, the bitstream header 531 of FIG. 5 may include scheduling information for scheduling the bitstream parsing process. Here, the scheduling information may include partial bitstream information and priority information, and may include the additional information when additional information required for scheduling exists. Once the scheduling is performed, the reordered bitstream can be assigned to three empty decoders.

540 illustrates an embodiment of a method for allocating the bitstream of FIG. 530 to the cores of three empty decoders.

Referring to 540 of FIG. 5, one representative probability unit bitstream may be classified and / or divided into a plurality of partial bitstreams. Here, one partial bitstream may include one or a plurality of minimum unit bitstreams. When the representative probability unit bitstream is divided into partial bitstreams, each entropy decoder is not a starting point of the entirety of the representative probability unit bitstream, but is located at the midpoint of the bitstream (e.g., the starting point of the partial bitstream) You can start parsing.

The decoder may determine a bitstream to be allocated to each bin decoder by rearranging the partial bitstreams so that binaries required for priority in the inverse binarization process can be parsed first considering the inverse binarization order of the syntax elements of the symbols. In this case, the decoder may allocate a bitstream so that a plurality of binarizers may have similar workloads in consideration of the number of empty encoders.

The scheduling information (partial bitstream information and priority information) necessary for performing the above-described scheduling process can be determined in an encoder. In the determination process, the encoder can determine the partial bit stream and the priority in consideration of the inverse binarization order of the syntax elements of the symbol. Once the scheduling information is determined, the entropy encoder may add the determined scheduling information to the header 531 of the bitstream and transmit it to the decoder.

Based on the transmitted scheduling information, the decoder can recognize a high-priority representative probability unit bitstream and / or a high-priority partial bitstream, and perform parsing on a partial bitstream basis. The decoder can perform scheduling for the bitstream parsing process based on the scheduling information, thereby minimizing the delay generated in the inverse binarization step.

According to the above-described method, smooth job distribution can be performed between a plurality of empty decoders included in the decoder, and delay in the inverse binarization step can be minimized. Therefore, the output delay in the parallel entropy decoder can be minimized, and the process of performing entropy decoding can be speeded up.

6 is a block diagram schematically showing an embodiment of a parallel entropy encoding apparatus according to the present invention.

A parallel entropy encoding apparatus according to the embodiment of FIG. 6 includes a binarizer 610, a probability estimator 620, a probability quantizer 630, a codeword length calculator 640, A mapping table calculator 650, an empty sequence calculator 660, a bin coder 670, a buffer 680 and a bit stream determiner 690. The parallel entropy encoding apparatus according to the embodiment of FIG. 6 may include a plurality of empty encoders 670 to perform parallel entropy encoding.

Referring to FIG. 6, the binarizer 610 may binarize each syntax element obtained in the encoding step. In this case, each syntax element can be converted into an empty sequence by the binarization process. Here, the empty sequence may be composed of a combination of 0 and 1. The probability estimator 620 can predict the LPB probability for each of the bins obtained by the binarization process.

The probability quantizer 630 can perform LPB probability quantization for each of the bins by dividing the probability interval to increase the coding efficiency. That is, the probability quantizer 630 can use the LPB probability of the predicted bin to determine which probability interval corresponds to each bin. For each bin, the probability quantizer 630 may determine a bin encoder 670 used for entropy encoding among a plurality of empty encoders, according to a probability interval corresponding to each bin.

The codeword length calculator 640 can derive and / or obtain an optimal codeword length (minimum length and maximum length) for each representative probability value, taking into account the coding efficiency. At this time, the codeword length calculator 640 may determine the minimum length and the maximum length of the codeword based on the characteristics of the representative probability value, in order to maintain the coding efficiency.

In one embodiment, information on the minimum length and maximum length of the derived codeword (codeword length information) may be included in the header of the bitstream and transmitted to the decoder. At this time, the decoder can use the codeword length information included in the header to determine the minimum length and the maximum length of the codeword parsed in each bin decoder.

In another embodiment, the maximum and minimum lengths of codewords for each representative probability may be derived using the same algorithm in the encoder and decoder. At this time, the maximum length and minimum length of the codeword can be derived based on the representative probability value of each empty encoder.

According to the above-described embodiment, the codeword length is limited to a certain range by the codeword length calculator 640, so that the parse rate for the bitstream can be improved.

The mapping table calculator 650 may use the codeword length information generated by the codeword length calculator 640 to select and / or generate a mapping table. Here, the mapping table may be used in a process in which an empty sequence is converted and / or mapped to a codeword. Thus, the mapping table may be referred to as a codeword-empty mapping table.

In one example, the minimum length and maximum length of the codeword may be a predetermined fixed value. At this time, a predetermined mapping table for each codeword length value within the range may be stored in the encoder and the decoder in the same manner. If the minimum length and the maximum length of the codeword are the same, a mapping table of one fixed length may be stored.

The encoder may select one of the stored mapping tables. Also, the encoder may add mapping table selection information, which indicates which mapping table is used among the stored mapping tables, to the header of the bitstream and transmit the mapping table selection information to the decoder. At this time, the decoder may select one mapping table among the plurality of mapping tables stored using the transmitted mapping table selection information.

As another example, the mapping table may be generated using the same generation algorithm in the encoder and the decoder. At this time, the encoder and the decoder can generate a mapping table corresponding to each codeword length within the codeword length range determined by the minimum length and the maximum length.

In addition to the generation algorithm, when additional information for generating the mapping table exists, the encoder may add the additional information to the header of the bitstream and transmit the additional information to the decoder. Here, the additional information may include information on the maximum length and the minimum length of the codeword, for example. At this time, the decoder can generate the mapping table using the information on the maximum length and the minimum length of the transmitted codeword.

In the above case, the encoder can select one of the generated mapping tables. Also, the encoder may add mapping table selection information, which indicates which mapping table is used among the generated mapping tables, to the header of the bitstream and transmit the mapping table selection information to the decoder. At this time, the decoder can select one mapping table among a plurality of mapping tables using the transmitted mapping table selection information.

Bin sequence calculator 660 can derive information about the binarization / inverse binarization sequence for the syntax elements of the symbol and information about the probability of each bin. The empty sequence calculator 660 can derive the scheduling information for the bitstream parsing process based on the derived information. Here, the scheduling may refer to a process of rearranging the bit streams in consideration of the inverse binarization order of the syntax elements of the symbols.

As described above with reference to FIG. 4, the scheduling information may include partial bitstream information and priority information, and may include the additional information if there is additional information required for scheduling. Here, the partial bitstream information represents information on the point at which the representative probability bitstream is divided into the partial bitstreams, and the priority information indicates priority of parsing for each representative probability bitstream and / Can be displayed.

As described above, the number of the empty encoders included in the encoder may be different from the number of the bin decoders included in the decoder, for example, the number of the bin decoders may be smaller than the number of the bin decoders. In this case, a bin having a high inverse binarization priority may be parsed later than a bin having a low inverse binarization priority, and a delay may occur in the inverse binarization process. In this case, the scheduling information derived from the empty sequence calculator 660 is used in the entropy decoding process, so that the delay occurring in the inverse binarization process can be minimized. The empty sequence calculator 660 may send the scheduling information to the bitstream determiner 690 to add and / or include the derived scheduling information to the header of the bitstream.

When the information derived from the codeword length calculator 640 and the empty sequence calculator 660 is used for entropy decoding, the output delay of the parallel entropy decoder can be minimized. Therefore, the entropy decoding process can be speeded up.

Empty coder 670 can perform entropy encoding for each bin using the mapping table derived by mapping table calculator 650. [ Each empty encoder 670 can convert the binarized bins into code words using a mapping table corresponding to the representative probability. The codeword output from the vacant encoder 670 may be stored in the buffer 680.

The codewords stored in the buffer may be transmitted to or stored in the decoder via the bitstream determiner 690. [ The bitstream determiner 690 may add header information to the header of the bitstream. For example, the header information may include codeword length information, mapping table selection information, information added for generating a mapping table, scheduling information, and the like. The bitstream determiner 690 may transmit the generated bitstream to the decoder. The decoder can minimize the decoding delay and improve the output speed by restricting the codeword length or rearranging the bitstream using the header information included in the transmitted bitstream.

7 is a block diagram schematically showing an embodiment of a parallel entropy decoding apparatus according to the present invention.

7 includes a codeword length calculator 710, a mapping table calculator 720, a bit stream decider 730, an empty decoder 740, a buffer 750, a probability quantizer 760, a probability predictor 770, and an inverse binarizer 780. [ The parallel entropy decoding apparatus according to the embodiment of FIG. 7 may include a plurality of bin decoders 740 to perform parallel entropy decoding.

Referring to FIG. 7, the codeword length calculator 710 may derive the codeword length information from the header of the bitstream transmitted from the encoder.

As described above, the length of the variable codeword causes an overhead in the process of bitstream parsing, so that the parsing speed can be reduced. In order to solve such a problem, a minimum length and a maximum length of a codeword can be determined for each representative LPB probability of a parallel entropy encoder in an encoder.

In one embodiment, information on the minimum length and maximum length of the derived codeword (codeword length information) may be included in the header of the bitstream and transmitted to the decoder. At this time, the decoder can use the codeword length information included in the header to determine the minimum length and the maximum length of the codeword parsed in each bin decoder.

In another embodiment, the maximum and minimum lengths of codewords for each representative probability may be derived using the same algorithm in the encoder and decoder. At this time, the maximum length and minimum length of the codeword can be derived based on the representative probability value of each empty encoder.

According to the above-described embodiment, the codeword length is limited to a certain range by the codeword length calculator 710, so that the parse rate for the bitstream can be improved.

The mapping table calculator 720 may select and / or generate a mapping table using the codeword length information derived by the codeword length calculator 710. [ At this time, the mapping table may be selected and / or generated based on the representative probability of each bin decoder 740.

In one example, the minimum length and maximum length of the codeword may be a predetermined fixed value. At this time, a predetermined mapping table for each codeword length value within the range may be stored in the encoder and the decoder in the same manner. If the minimum length and the maximum length of the codeword are the same, a mapping table of one fixed length may be stored.

The encoder may select one of the stored mapping tables. Also, the encoder may add mapping table selection information, which indicates which mapping table is used among the stored mapping tables, to the header of the bitstream and transmit the mapping table selection information to the decoder. At this time, the decoder may select one mapping table among the plurality of mapping tables stored using the transmitted mapping table selection information.

As another example, the mapping table may be generated using the same generation algorithm in the encoder and the decoder. At this time, the encoder and the decoder can generate a mapping table corresponding to each codeword length within the codeword length range determined by the minimum length and the maximum length.

In addition to the generation algorithm, when additional information for generating the mapping table exists, the encoder may add the additional information to the header of the bitstream and transmit the additional information to the decoder. Here, the additional information may include, for example, information on the maximum length and the minimum length of the codeword, and the maximum length and the minimum length of the codeword may be determined for each representative LPB probability of the parallel entropy encoder . At this time, the decoder can generate the mapping table using the information on the maximum length and the minimum length of the transmitted codeword.

In the above case, the encoder can select one of the generated mapping tables. Also, the encoder may add mapping table selection information, which indicates which mapping table is used among the generated mapping tables, to the header of the bitstream and transmit the mapping table selection information to the decoder. At this time, the decoder can select one mapping table among a plurality of mapping tables using the transmitted mapping table selection information.

In the above-described embodiment, the mapping table is determined using the codeword length information transmitted from the encoder. Thus, the length of the codeword for each representative probability can be limited, the delay of the parsing process is minimized, and the output speed of the bin decoder 740 can be improved.

The bitstream determiner 730 can decode the header information contained in the header of the bitstream transmitted from the encoder. The header information may include, for example, scheduling information (partial bitstream information and / or priority information). The bitstream determiner 730 may classify each representative probability bitstream into a partial bitstream using the scheduling information and perform scheduling on the bitstream input to the bin decoder 740. At this time, the decoder may allocate the bit stream to the bin decoder so that a plurality of bin decoders may have a similar work amount in consideration of the number of bin decoders. A specific embodiment of the scheduling method has been described above with reference to FIG. 4 and FIG. 5, and therefore will not be described.

The bitstream determiner 730 can minimize the input delay in the inverse binarization step by performing the scheduling on the bitstream using the scheduling information transmitted from the encoder.

When the information derived from the codeword length calculator 710 and the bitstream decider 730 is used for entropy decoding, the output speed of the parallel entropy decoder can be improved. Therefore, the entropy decoding process can be speeded up.

Each bin decoder 740 may convert the codeword into an empty sequence using a mapping table corresponding to the scheduled bitstream and the representative probability. At this time, the bit stream input to each bin decoder 740 may be determined according to the representative LPB probability, for example.

The bins output from the binarizer 740 may be input to the probability estimator 770 through the buffer 750 and the probability quantizer 760 in order. The probability estimator 770 can derive the LPB probability for the input bin. The empty sequence may be decoded into a value of the meaningful syntax element via the inverse binarizer 780 after passing through the probability predictor 770.

8 is a block diagram schematically showing another embodiment of the parallel entropy encoding apparatus according to the present invention.

The parallel entropy encoding apparatus according to the embodiment of FIG. 8 includes a binarizer 810, a probability estimator 820, a probability quantizer 830, a codeword length calculator 840, a mapping table calculator 850, An encoder 860 and a buffer 870. The parallel entropy encoding apparatus according to the embodiment of FIG. 8 may include a plurality of empty encoders 860 to perform parallel entropy encoding.

As described above, the encoder can limit the length of the codeword in order to reduce the overhead incurred in the parsing process and improve the output speed of the decoder. When a predetermined fixed length codeword is used, the coding efficiency may be reduced, so that the encoder can determine the minimum length and the maximum length of the codeword for each of the empty encoder and / or the bin decoder.

Referring to FIG. 8, the codeword length calculator 840 may derive and / or obtain an optimum codeword length (minimum length and maximum length) for each representative probability value of the empty encoder, taking into consideration the coding efficiency have. At this time, the codeword length calculator 840 can determine the minimum length and the maximum length of the codeword based on the characteristics of the representative probability, in order to maintain the coding efficiency.

In the embodiment of FIG. 8, the operation of the remaining configuration except for the above-mentioned configuration is the same as in the embodiment of FIG.

9 is a block diagram schematically showing another embodiment of a parallel entropy decoding apparatus according to the present invention.

9 includes a codeword length calculator 910, a mapping table calculator 920, a bin decoder 930, a buffer 940, a probability quantizer 950, (960) and an inverse binarizer (970). The parallel entropy decoding apparatus according to the embodiment of FIG. 9 may include a plurality of bin decoders 930 to perform parallel entropy decoding. The parallel entropy decoding apparatus according to the embodiment of FIG. 9 can operate similarly to the parallel entropy decoding apparatus according to the embodiment of FIG.

The bit stream transmitted from the encoder may be allocated to a plurality of bin decoders 930 included in the decoder. At this time, the decoder can determine a bitstream allocated to each bin decoder using the header information included in the header of the transmitted bitstream. At this time, due to the length of the variable codeword, overhead may occur in the bitstream parsing process and the parsing rate may be reduced. In order to solve such a problem, the codeword length calculator 910 can determine the minimum length and the maximum length of the codeword for each representative LPB probability of the parallel entropy encoder.

In one embodiment, information on the minimum length and maximum length (codeword length information) of the codeword derived from the encoder may be included in the header of the bitstream and transmitted to the decoder. At this time, the codeword length calculator 910 can determine the minimum length and the maximum length of the codeword to be parsed by each bin decoder using the codeword length information included in the header.

In another embodiment, the maximum and minimum lengths of codewords for each representative probability may be derived using the same algorithm in the encoder and decoder. At this time, the maximum length and minimum length of the codeword can be derived based on the representative probability value of each empty encoder.

The mapping table calculator 920 uses information on the representative probability of each bin decoder 930 and information on the minimum and maximum lengths of codewords determined by the codeword length calculator 910 , The mapping table can be determined. A specific embodiment of the mapping table determination method has been described above with reference to FIG. 7, and therefore, the description thereof will be omitted.

By the codeword length calculator 910 and the mapping table calculator 920 described above, the output speed of the parallel entropy decoder can be improved. Therefore, the entropy decoding process can be speeded up.

In the embodiment of FIG. 9, the operation of the remaining configuration except for the above-described configuration is the same as in the embodiment of FIG.

10 is a block diagram schematically showing another embodiment of the parallel entropy encoding apparatus according to the present invention.

The parallel entropy encoding apparatus according to the embodiment of FIG. 10 includes a binarizer 1010, a probability estimator 1020, a probability quantizer 1030, an empty sequence calculator 1040, a bin encoder 1050, a buffer 1060 and a bit stream determiner 1070. [ The parallel entropy encoding apparatus according to the embodiment of FIG. 10 may include a plurality of empty encoders 1050 to perform parallel entropy encoding.

Referring to FIG. 10, each syntax element obtained in the binarizer 1010 encoding step may be binarized. In this case, each syntax element can be converted into an empty sequence by the binarization process. The probability estimator 1020 can calculate the probability of occurrence for each of the bins obtained by the binarization process. The probability quantizer 1030 may also divide the probability interval and perform LPB probability quantization for each of the bins.

The empty sequence calculator 1040 can derive the scheduling information for the bitstream parsing process. As described above with reference to FIG. 4, the scheduling information may include partial bitstream information and priority information, and may include the additional information if there is additional information required for scheduling. Here, the partial bitstream information represents information on the point at which the representative probability bitstream is divided into the partial bitstreams, and the priority information indicates priority of parsing for each representative probability bitstream and / Can be displayed.

As described above, in the parsing process, a bin having a high inverse binarization priority can be parsed later than a bin having a low inverse binarization priority. In this case, a delay may occur in the inverse binarization process. In this case, since the scheduling information derived from the empty sequence calculator 1040 is used for the entropy decoding process, the delay occurring in the inverse binarization process can be minimized. The empty sequence calculator 1040 may send the scheduling information to the bitstream determiner 1070 to add and / or include the derived scheduling information to the header of the bitstream. The bitstream determiner 1070 may add the scheduling information to the header of the bitstream, and the bitstream may be transmitted to the decoder.

By the above-described bin sequence calculator 1040, the output speed of the parallel entropy decoder can be improved. Therefore, the entropy decoding process can be speeded up.

In the embodiment of FIG. 10, the operation of the remaining configuration except for the above-described configuration is the same as in the embodiment of FIG.

11 is a block diagram schematically showing another embodiment of a parallel entropy decoding apparatus according to the present invention.

The entropy decoding apparatus according to the embodiment of FIG. 11 includes a bitstream decider 1110, a bin decoder 1120, a buffer 1130, a probability quantizer 1140, a probability predictor 1150, and an inverse binarizer 1160). The parallel entropy decoding apparatus according to the embodiment of FIG. 11 may include a plurality of bin decoders 930 to perform parallel entropy decoding. The parallel entropy decoding apparatus according to the embodiment of FIG. 11 can operate similar to the parallel entropy decoding apparatus according to the embodiment of FIG.

The bitstream determiner 1110 can decode the header information contained in the header of the bitstream transmitted from the encoder. The header information may include, for example, scheduling information (partial bitstream information, priority information, and / or additional information needed for bitstream reordering). The bitstream decider 1110 may classify each representative probability bitstream into a partial bitstream using the scheduling information and perform scheduling on a bitstream input to the bin decoder 1120. [ In this case, the decoder may determine a bitstream to be allocated to each bin decoder so that a plurality of binarizers may have similar workloads, considering the number of binarizers.

The bitstream determiner 1110 can minimize the input delay in the inverse binarization step by performing the scheduling on the bitstream using the scheduling information transmitted from the encoder.

*

In the embodiment of FIG. 11, the operation of the remaining configuration except for the above-described configuration is the same as in the embodiment of FIG.

12 is a flowchart schematically showing an embodiment of a parallel entropy encoding method according to the present invention.

Referring to FIG. 12, the encoder may convert syntax elements into an empty sequence using a predetermined binarization method (S1210). Here, the empty sequence may be composed of a combination of 0 and 1, and each 0 or 1 may be called a bin.

The encoder may determine the LPB probability for each bin bin (S1220), and may divide the bin probability interval according to the quantization interval (S1230).

In addition, the encoder may derive the scheduling information in order to minimize the input delay in the inverse binarization step of the decoder (S1240). As described above, the scheduling information may include partial bitstream information and priority information, and may include the additional information if there is additional information required for scheduling. The derived scheduling information may be included in the header of the bitstream and transmitted to the decoder.

As described above, the bin probability interval may be divided according to the quantization interval, and each divided probability interval may be allocated to a bin coder corresponding to each probability interval. The encoder may determine an empty encoder to be used for entropy encoding of each bin through quantization according to a probability interval corresponding to each bin (S1250).

The encoder can derive the codeword length information for each representative LPB probability of the empty encoder by a predetermined algorithm (S1260). Here, the codeword length information may be information on a minimum length and a maximum length of a codeword, for example. When the codeword length information is derived, the encoder can determine the mapping table using the derived codeword length information. Here, the mapping table may refer to a table used in the process of converting an empty sequence into a codeword and / or mapping.

The encoder may perform bin coding for each bin using the determined mapping table (S1270). The encoder can convert binarized bins into code words by performing bin coding. The output codeword is included in the bitstream and can be transmitted to the decoder in NAL units.

13 is a flowchart schematically illustrating an embodiment of a parallel entropy decoding method according to the present invention.

Referring to FIG. 13, the decoder may receive a bitstream from an encoder (S1310). The header of the received bitstream may include header information. Here, the header information may include, for example, codeword length information, mapping table selection information, information added for generating a mapping table, and scheduling information.

The decoder may derive the scheduling information from the header of the bitstream. In order to minimize the input delay in the inverse binarization step, the decoder may perform the scheduling for the bitstream using the derived scheduling information (S1320). Here, the scheduling may refer to a process of rearranging the bit streams in consideration of the inverse binarization order of the syntax elements of the symbols. At this time, the decoder may allocate the bit stream to the bin decoder so that a plurality of bin decoders may have a similar work amount in consideration of the number of bin decoders.

Referring again to FIG. 13, the decoder may derive codeword length information from the header of the bitstream transmitted from the encoder (S1330). Here, the codeword length information may mean information on a minimum length and a maximum length of a codeword corresponding to a representative LPB probability of each bin decoder. When the codeword length information is derived, the decoder can determine the mapping table using the derived codeword length information.

The decoder may perform bin decoding for each bin using the determined mapping table (S1340). At this time, the plurality of binarizers included in the decoder may decode the bin corresponding to the probability interval allocated to each bin. The decoder can convert the codeword into a bean by performing bin decoding.

After passing through the probability quantization step, the decoder may determine the LPB probability for each bin output from the bin decoder (S1350). Also, the decoder may perform inverse binarization on each bin output from the bin decoder to derive a value of a meaningful syntax element (S1360).

In the above-described embodiments, the methods are described on the basis of a flowchart as a series of steps or blocks, but the present invention is not limited to the order of the steps, and some steps may occur in different orders or simultaneously . It will also be understood by those skilled in the art that the steps depicted in the flowchart illustrations are not exclusive and that other steps may be included or that one or more steps in the flowchart may be deleted without affecting the scope of the invention You will understand.

The above-described embodiments include examples of various aspects. While it is not possible to describe every possible combination for expressing various aspects, one of ordinary skill in the art will recognize that other combinations are possible. Accordingly, it is intended that the invention include all alternatives, modifications and variations that fall within the scope of the following claims.

Claims (3)

The method comprising: receiving a bitstream for an image;
Decoding the decodable position information of each of the plurality of partial bit streams in the received bit stream, wherein the number of the plurality of partial bit streams is determined based on the number of the decodable position information, The start point or end point of each of the partial bitstreams is determined based on decodable position information of each of the plurality of partial bitstreams;
Entropy decoding the plurality of partial bit streams separated based on decodable position information of each of the plurality of partial bit streams; And
Obtaining a syntax element based on the entropy-decoded partial bitstream, and decoding the image based on the obtained syntax element.
Encoding an image to obtain a syntax element;
Determining decodable position information; And
And generating a bitstream including the syntax element and the decodable position information,
Wherein the bitstream comprises a plurality of partial bitstreams,
Wherein the number of partial bitstreams is determined based on the number of decodable position information, and a starting point or an ending point of each of the plurality of partial bitstreams is determined as decodable position information of each of the plurality of partial bitstreams Based on the number of pictures.
A recording medium storing a bit stream generated by a video encoding method,
The image encoding method includes:
Encoding an image to obtain a syntax element;
Determining decodable position information; And
And generating a bitstream including the syntax element and the decodable position information,
Wherein the bitstream comprises a plurality of partial bitstreams,
Wherein the number of partial bitstreams is determined based on the number of decodable position information, and a starting point or an ending point of each of the plurality of partial bitstreams is determined as decodable position information of each of the plurality of partial bitstreams And the bit stream is determined based on the bit stream.

Images