WO2005086357A1 - 符号化データの復号プログラム及び方法並びに装置 - Google Patents
符号化データの復号プログラム及び方法並びに装置 Download PDFInfo
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- WO2005086357A1 WO2005086357A1 PCT/JP2004/002940 JP2004002940W WO2005086357A1 WO 2005086357 A1 WO2005086357 A1 WO 2005086357A1 JP 2004002940 W JP2004002940 W JP 2004002940W WO 2005086357 A1 WO2005086357 A1 WO 2005086357A1
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- 238000000034 method Methods 0.000 title claims abstract description 45
- 239000013598 vector Substances 0.000 claims abstract description 169
- 238000013139 quantization Methods 0.000 claims description 38
- 230000008569 process Effects 0.000 claims description 11
- 238000006243 chemical reaction Methods 0.000 claims description 6
- 230000006835 compression Effects 0.000 claims description 6
- 238000007906 compression Methods 0.000 claims description 6
- 230000009467 reduction Effects 0.000 claims description 6
- 238000010586 diagram Methods 0.000 description 10
- 238000012545 processing Methods 0.000 description 9
- 230000008859 change Effects 0.000 description 3
- 230000009466 transformation Effects 0.000 description 3
- 238000013459 approach Methods 0.000 description 2
- 230000007423 decrease Effects 0.000 description 2
- 230000002427 irreversible effect Effects 0.000 description 2
- 241000282412 Homo Species 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000000717 retained effect Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 230000001131 transforming effect Effects 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/44—Decoders specially adapted therefor, e.g. video decoders which are asymmetric with respect to the encoder
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
- H04N19/124—Quantisation
- H04N19/126—Details of normalisation or weighting functions, e.g. normalisation matrices or variable uniform quantisers
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
- H04N19/18—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being a set of transform coefficients
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/60—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
Definitions
- the present invention relates to a coded data decoding program, method and apparatus.
- the present invention relates to a coded data decoding program, a method and an apparatus for receiving a signal encoded by lossy compression and outputting the decoded signal.
- the reproduced signal is distorted using the fact that the human visual / auditory characteristics are insensitive to small distortion.
- Allowing only compression allows for greater compression.
- Such an encoding method is called lossy encoding because it does not accurately reproduce the original signal.
- FIG. 8 is a block diagram showing a decoding device for JPEG (Joint Photographic Experts Group) coded data widely used, for example, as image coding. IEEE Transactions on Consumer Electronics, 21 February, 1992 It was disclosed on the page.
- the decoding device shown in FIG. 8 includes a variable-length decoder 80 that inputs an encoded stream, an inverse quantizer 81, an inverse DCT (Discrete Cosine Transform) transformer 82, a limiter 83, And an integerizer 84.
- the limiter 83 and the integerizer 84 are not disclosed in the above-mentioned documents, they are widely used in general and added to the following description because they are important.
- the decoder may perform the reverse process.
- a variable-length decoder 80 decodes a JPEG stream into a DCT coefficient quantization index.
- the inverse quantizer 81 decodes this quantization index into a DCT coefficient.
- the inverse 13 ⁇ converter 82 performs an inverse transform on the DCT coefficient to reproduce the original signal.
- the output of the inverse DCT converter 82 is a real number, and when a reproduced signal is represented digitally, it must be converted into a discrete signal within a certain range. This conversion is performed by the limiter 83 and the integerizer 84.
- the limiter 83 clips the output of the inverse DCT converter 82 to a predetermined range, and the integerizer 23 converts the result to an integer.
- the process of clipping and integerization is The order may be reversed.
- an output in a format that can be expressed as digital data is obtained as the output of the integerizer 84.
- the above processing is performed for each block, and finally, all blocks are integrated to obtain decoded data.
- the processing in the limiter 83 and the integerizer 84 is a many-to-one mapping, the original DCT coefficients cannot be restored from its output. This means that some information of the quantization index of the DCT coefficient represented as a stream is lost by decoding.
- Another problem is that information embedded in the quantized DCT coefficients is lost due to errors caused by clipping and integerization.
- the present invention has been made in order to solve such a problem, and a coded data decoding program, method and apparatus capable of completely restoring an original stream when decoded data is coded again.
- the purpose is to provide.
- a coded data decoding program and method capable of maintaining the structure of a signal represented as a stream within a certain range of quantization accuracy and completely retaining information embedded in quantized DCT coefficients. And to provide the device. Disclosure of the invention
- An encoded data decoding apparatus and method are configured to input an irreversibly-compressed encoded signal, and to convert an arbitrary real number vector into one in a first vector space in which the decoded signal exists. Determining whether the convex projection has converged via the first projecting means (or step) for orthogonally projecting the convex set X, and determining whether the convex projection has converged through the first projecting means (or step) The real number belonging to the set X Convergence determining means (or step) for obtaining a vector X and outputting it as a decoded signal; and, when it is determined that the convex projection is not converged, the arbitrary vector in the first vector space is converted to the first vector.
- a second projection means for repeating orthogonal projection to the set X and the set Y is provided.
- an encoded data decoding program causes a computer to function as each stage of an encoded data decoding device.
- FIG. 1 is a diagram for explaining the approach of the present invention, and is a diagram schematically showing an example in which the value of a quantization index changes by clipping a decoded transform coefficient,
- FIG. 2 illustrates Embodiment 1 of the present invention.
- FIG. 2 illustrates Embodiment 1 of the present invention.
- FIG. 1 is a block diagram showing a case where a coded data decoding device as hardware for explaining a coded data decoding program and method according to the present invention is configured by a computer;
- FIG. 5 is a flowchart showing the contents of a program for decoding encoded data, which is stored in R ⁇ M 4B of FIG. 4 and operates based on the control of CPU 4A,
- FIG. 6 corresponds to the flowchart shown in FIG. 5, and is a block diagram showing a functional configuration of the encoded data decoding device according to the present invention.
- FIG. 7 illustrates the second embodiment of the present invention, in which a vector y e obtained by inversely quantizing the quantized index of transmitted DCT coefficients by Q e is used as an initial value, and a set X and a set Y are set.
- a diagram showing how the convex projection is repeated between and the vector xn that is a common element is obtained.
- FIG. 8 is a block diagram showing a conventional encoded data decoding device. BEST MODE FOR CARRYING OUT THE INVENTION
- FIG. 1 schematically shows an example in which the value of the quantization index changes as the decoded transform coefficient is clipped.
- y c is a vector of quantized DCT coefficients, which is a vector known at the time of decoding. This vector is a vector obtained at the output of the inverse quantizer 81 in FIG.
- Y represents a set of DCT coefficient vectors quantized to y c .
- y c is converted to a signal in the time domain by the inverse DCT converter 82, and then tapped by the limiter 83 to a range of constant values.
- X represents a set of vectors in such a range of values.
- the processing of the limiter 83 is inverse DCT y. Can be regarded as the process of orthogonally projecting the set X.
- the output vector of the limiter 8 3 and Table with x Q is the output vector of the limiter 8 3 and Table with x Q.
- this vector is a real vector, it is converted to an integer to obtain the final decoded vector xd .
- the vector x d is decoded out of the set Y by clipping. This means that if the vector x d is re-encoded, its quantized vector will not match y c and the information of the quantized DCT coefficients will be lost by decoding.
- the present invention utilizes a convex projection method for decoding an encoded stream.
- the convex projection method is an arbitrary set when the two sets X and Y are both convex sets, that is, a point on a line segment whose ends are two elements belonging to the set also belongs to that set.
- the common solution is obtained by repeating orthogonal projections on sets X and Y starting from the initial value of.
- Figure 2 shows that by orthogonally projecting the set X and the set Y to two sets of vectors and Y, each component of which can take a finite range, with y e as the initial value, The vector x 0 , X l , ... , Are obtained in this order.
- X i becomes as close as possible to the beta x n that belongs to the sets X and Y in common.
- the sets X and Y are clearly convex sets, since their components are defined as sets with a certain range. Therefore, the common solution ⁇ ⁇ can always be determined.
- the set W is defined as a set of vectors in which the range of possible values of each component is finite.For example, a set obtained by reducing the range of each component of the set Y by k (k ⁇ 1) times do it. Repeating the orthogonal projection between the set X and the set w with y c as the initial value reveals that another vector X ⁇ that is deeper than ⁇ is searched for.
- FIG. 4 is a block diagram in the case where an encoded data decoding apparatus as hardware for explaining an encoded data decoding program and method according to the present invention is configured by a computer.
- the hardware configuration of the coded data decoding device 4 shown in FIG. 4 includes a CPU 4A, a ROM 4B for storing a coded data decoding program as a processing program, fixed data, and the like, and processing data and input data. And an input / output unit 4D.
- the CPU 4A receives a signal irreversibly compressed and coded and decodes the coded data stored in the ROM 4B. The result processed based on the control is output as a decoded signal.
- FIG. 5 shows a flowchart of a coded data decoding program stored in the ROM 4B and operated under the control of the CPU 4A.
- the quantization index y q of the received DCT coefficient is inversely quantized to obtain an initial vector y for convex projection. Also, set the value of k to 1. That is, the processing represented by the following equation is performed.
- Q- 1 ( ⁇ ) indicates the operation of inverse quantization.
- the vector y is subjected to an inverse transformation and then orthogonally projected to the set X.
- the orthogonal projection to the set X can be performed by clipping each component of the vector obtained by inversely transforming y to a range from a to b (a ⁇ b). , Components smaller than a are changed to a, components larger than b are changed to b The other components may be left as they are.
- T 1 ( ⁇ ) represents the inverse transformation
- P x ( ⁇ ) represents the orthogonal projection to the set X.
- the convergence determination step S53 it is checked whether or not the vector has changed due to the orthogonal projection to the set X. If the change is small, it is determined that the convex projection has converged, and the process proceeds to the integerization step S55. If the change is large, proceed to the projection step S54.
- the magnitude of the change is, for example,
- I.I is the Euclidean norm of the vector and ⁇ is a positive number determined by the precision of the arithmetic circuit.
- a projection step S54 XT is DCT-transformed to obtain ⁇ (X) ( ⁇ (-) represents DCT transformation), and this is orthogonally projected to a set kY.
- the orthogonal projection it is to be equal to y c, each component of T (X) may be modified to a certain extent when quantizing the T (X). This modification can be performed in the same manner as in the projection step S52.
- the processing of the projection step S54 is
- an end determination step S56 it is confirmed whether or not this integer vector belongs to the set Y, and if so, this vector is set as an output vector and decoding is ended.
- This end decision can be made by checking whether or not the result of quantizing the integer vector after the DCT transform of the integer vector matches y c . That is,
- x is an element of the set Y.
- int ( ⁇ ) is an integer and Q (-) is a quantization operator.
- the processing of the projection step S 58 is the same as that of the projection step S 54.
- the processing is exactly the same.
- FIG. 6 is a block diagram corresponding to the flowchart for explaining the above-described encoded data decoding program and method shown in FIG. 5, and showing a functional configuration of the encoded data decoding apparatus according to the present invention.
- First projection means 6 1 for orthogonally projecting a real number vector onto one convex set X, and whether or not the convex projection has converged via the first projection means 6 1 is determined, and it is determined that the convex projection has converged.
- Convergence judging means 62 that obtains the real vector X belonging to the set X and outputs it as a decoded signal, and if it is judged that the convex projection has not converged, Is orthogonally projected onto one convex set Y in a second vector space different from the first vector space, and then transferred to the first projecting means 61, where the encoded signal is initialized to the initial value.
- a second projection that repeats orthogonal projections on sets X and Y And means 6 3.
- the decoding device for the encoded data converts the real vector belonging to the set X into an integer vector.
- the end determination means 65 that determines whether the integer vector belongs to the set Y and outputs the integer vector as the decryption vector when it is determined that the integer vector belongs to the set Y. If it is determined, the reducing means 66 reduces the set Y to generate a new convex set W which is a subset of the set Y, and orthogonally projects the transformed integer vector onto the convex set W.
- the first projecting means 6 is shifted to the first projecting means 6 1, and the orthogonal projection is performed between the set W and the set X using the coded signal as an initial value to repeatedly correct the real number vector X.
- each functional configuration shown in FIG. 6 corresponds to each step in the flowchart shown in FIG. That is, the first projection means 61 corresponds to the projection step S52, the convergence determination means 62 corresponds to the convergence determination step S53, and the second projection means 63 corresponds to the projection step S54.
- the integer conversion means 64 corresponds to the integer conversion step S 55, the end determination means 65 corresponds to the end determination step S 56, the reduction means 66 corresponds to the reduction step S 57,
- the third projection means 67 corresponds to the projection step S58.
- the convergence of the method of the present invention has not been proven. That is, even if k is made sufficiently small, the termination is not determined in the termination determination step S56, and an integer vector that exists in common in the sets X and Y may not be found. This is particularly likely to occur when the quantization is fine. Because the quantization becomes finer Therefore, the size of the set Y decreases, and consequently, the integer vectors included in the intersection ⁇ decrease.
- the present invention also determines a quantization vector having a different precision from the quantization vector of the encoding, particularly when the quantization is fine, and sets the DC vector encoded within the range of the quantization precision.
- ⁇ Give a decoding method that holds the information held by the coefficients.
- the program, method, and apparatus for decoding encoded data according to the second embodiment of the present invention have the same configuration as the first embodiment shown in FIGS. You need to do different things in some steps.
- a quantization vector for determining that the structure of encoded data is maintained separately from the quantization vector for encoding is used.
- This quantization vector is Q w
- the quantization vector for encoding is Q e .
- the set X is defined as in the first embodiment.
- the set Y is defined as a set of DCT coefficient vectors whose result when quantized by Q w is y w .
- Q w is set so that there is a sufficient number of integer vectors in the set Y.
- Figure 7 shows that the vector y c obtained by inversely quantizing the transmitted DCT coefficient quantization index with Q c is used as the initial value, and the convex projection is repeated between set X and set Y. This shows how a certain vector xn is obtained.
- y c is an element of the set Y.
- the initial value of the vector y is obtained using Q c and the set Y is defined using Q w Good.
- initialization step 5 as an initial value of y, obtaining the initial value of the vector y with Q c. That is,
- the projection step S52, the convergence determination step S53, the projection step S54, and the integerization step S55 are the same as those in the first embodiment.
- the end determination step S56 is a quantum Using Q w as the optimization parameter, the end is determined by checking whether the following equation holds.
- x is the output vector of the projection step S52.
- the reduction step S57 and the projection step S58 are the same as in the first embodiment.
- the embodiment above again DCT transform decoding Betatoru, the result of which was quantized by Q w, so consistent with the results obtained by quantizing the original encoded data Q w, encoded data
- the structure of is preserved in the decoded signal within the precision of Q w . Therefore, for example, information such as a digital watermark can be left in the decoded data with an accuracy of Q w .
- Q w quantization width vector
- n indicates the number of times k has been modified, and the value of k corresponding to n is shown in the second column.
- the experiment was performed by setting Q c in three ways and changing the encoding accuracy. table 1
- the accuracy of this encoding is represented by the parameter q.
- q l.0
- Q W Q C holds.
- Image 1 is a natural image
- image 2 is a wedge test image.
- the total number of DCT blocks in these images is 81920 and 2304, respectively.
- the present invention is not limited to the image encoding but can be applied to encoded data such as audio.
- the set Y By giving the set Y appropriately, it can be applied not only to the DCT transform but also to other encoding methods such as the wavelet transform.
- the present invention can be applied not only to encoding of still images but also to encoding of moving images such as MPEG.
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US10/584,188 US8000394B2 (en) | 2004-03-08 | 2004-03-08 | Program, method, and apparatus for decoding coded data |
PCT/JP2004/002940 WO2005086357A1 (ja) | 2004-03-08 | 2004-03-08 | 符号化データの復号プログラム及び方法並びに装置 |
JP2006510590A JP4323519B2 (ja) | 2004-03-08 | 2004-03-08 | 符号化データの復号プログラム及び方法並びに装置 |
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US8180167B2 (en) * | 2008-07-16 | 2012-05-15 | Seiko Epson Corporation | Model-based error resilience in data communication |
CN102265616B (zh) * | 2008-12-26 | 2013-12-11 | 日本电气株式会社 | 逆量化方法和逆量化装置 |
KR102184074B1 (ko) * | 2013-08-05 | 2020-11-27 | 엘지전자 주식회사 | 셀룰러 네트워크에서 간섭 정렬 방법 및 장치 |
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JPH08149477A (ja) * | 1994-11-22 | 1996-06-07 | Sony Corp | 画像符号化装置および画像復号化装置 |
WO2002093935A1 (en) * | 2001-05-10 | 2002-11-21 | Matsushita Electric Industrial Co., Ltd. | Image processing apparatus |
JP2003244701A (ja) * | 2002-02-21 | 2003-08-29 | Matsushita Electric Ind Co Ltd | 画像処理装置および画像処理方法 |
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IL104636A (en) * | 1993-02-07 | 1997-06-10 | Oli V R Corp Ltd | Apparatus and method for encoding and decoding digital signals |
US6201550B1 (en) * | 1997-06-30 | 2001-03-13 | Fuji Xerox Co., Ltd. | Image forming apparatus and method of generating gradation pattern |
KR100269125B1 (ko) * | 1997-10-25 | 2000-10-16 | 윤덕용 | 양자화효과감소를위한영상데이터후처리방법및장치 |
JP3705923B2 (ja) * | 1998-04-09 | 2005-10-12 | 株式会社ソニー・コンピュータエンタテインメント | 画像処理装置および画像処理方法、プログラム提供媒体、並びにデータ提供媒体 |
US7194138B1 (en) * | 1998-11-04 | 2007-03-20 | International Business Machines Corporation | Reduced-error processing of transformed digital data |
JP2003024470A (ja) | 2001-07-13 | 2003-01-28 | Yamaha Motor Co Ltd | 水中推進機 |
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JPH08149477A (ja) * | 1994-11-22 | 1996-06-07 | Sony Corp | 画像符号化装置および画像復号化装置 |
WO2002093935A1 (en) * | 2001-05-10 | 2002-11-21 | Matsushita Electric Industrial Co., Ltd. | Image processing apparatus |
JP2003244701A (ja) * | 2002-02-21 | 2003-08-29 | Matsushita Electric Ind Co Ltd | 画像処理装置および画像処理方法 |
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US8000394B2 (en) | 2011-08-16 |
JPWO2005086357A1 (ja) | 2008-01-24 |
JP4323519B2 (ja) | 2009-09-02 |
US20070122044A1 (en) | 2007-05-31 |
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