JP5006774B2 - Encoding method, decoding method, apparatus using these methods, program, and recording medium - Google Patents

Encoding method, decoding method, apparatus using these methods, program, and recording medium Download PDF

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JP5006774B2
JP5006774B2 JP2007314034A JP2007314034A JP5006774B2 JP 5006774 B2 JP5006774 B2 JP 5006774B2 JP 2007314034 A JP2007314034 A JP 2007314034A JP 2007314034 A JP2007314034 A JP 2007314034A JP 5006774 B2 JP5006774 B2 JP 5006774B2
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健弘 守谷
登 原田
優 鎌本
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Nippon Telegraph and Telephone Corp
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本発明は、対数近似圧伸ＰＣＭなどの圧伸された信号列の符号化方法、復号化方法、これらの方法を用いた装置、プログラム、記録媒体に関する。   The present invention relates to an encoding method and decoding method for a signal sequence that has been decompressed, such as logarithmic approximate companding PCM, and an apparatus, program, and recording medium using these methods.

音声、画像などの情報を圧縮する方法として歪の無い可逆の符号化が知られている。波形をそのまま線形ＰＣＭ信号として記録した場合には各種の圧縮符号化が考案されている（非特許文献１）。
一方、電話の長距離伝送やＶｏＩＰ用の音声伝送には、振幅をそのままの数値とする線形ＰＣＭではなく、振幅を対数に近似させた対数近似圧伸ＰＣＭ（非特許文献２）などが使われている。
MatHans, “Lossless Compression of Digital Audio”, IEEE SIGNAL PROCESSING MAGAZINE, July 2001, pp.21-32. ITU-T Recommendation G.711, “Pulse Code Modulation (PCM) of Voice Frequencies”. As a method for compressing information such as sound and image, lossless encoding without distortion is known. When the waveform is recorded as a linear PCM signal as it is, various compression encodings have been devised (Non-patent Document 1).
On the other hand, for long-distance transmission of telephones and voice transmission for VoIP, logarithmic approximate companding PCM (Non-patent Document 2) in which the amplitude is approximated to a logarithm is used instead of the linear PCM with the amplitude as it is. ing.
MatHans, “Lossless Compression of Digital Audio”, IEEE SIGNAL PROCESSING MAGAZINE, July 2001, pp.21-32. ITU-T Recommendation G.711, “Pulse Code Modulation (PCM) of Voice Frequencies”.

一般の電話に代わってＶｏＩＰシステムが普及してくると、ＶｏＩＰ用の音声伝送のために求められる伝送容量は増大する。たとえば、非特許文献２のＩＴＵ−Ｔ Ｇ．７１１の場合であれば、１回線に対して６４ｋｂｉｔ／ｓ×２の伝送容量が必要だが、回線数が増えれば求められる伝送容量も増大する。したがって、対数近似圧伸ＰＣＭなどの圧伸された信号列を圧縮符号化する技術（符号量を低減できる技術）が求められる。圧伸とは、元の信号列の大小関係を番号系列で示すことを意味している。また、元の信号列の大小関係を示す番号系列とは、大小関係を維持したまま、あるいは大小関係を反転して、均等間隔に付された数である。図１は、第２信号列の振幅の例を示す図である。横軸は線形ＰＣＭの場合の値であり、縦軸は対数近似圧伸ＰＣＭの場合の対応する値である。図２は、８ビットのμ則の具体的な形式を示す図である。正負を示す１ビット（極性）、指数を示す３ビット（指数部）、線形符号での増分（傾き）を示す４ビット（線形部）から構成されている。この形式の対数近似圧伸ＰＣＭの場合、−１２７から１２７までの数値を表現できる。これは、線形ＰＣＭの−８１５８から８１５８までに相当する（図１）。   When a VoIP system becomes widespread instead of a general telephone, the transmission capacity required for voice transmission for VoIP increases. For example, ITU-T G. In the case of 711, a transmission capacity of 64 kbit / s × 2 is required for one line, but the required transmission capacity increases as the number of lines increases. Accordingly, there is a need for a technique (a technique that can reduce the amount of code) that compresses and encodes a stretched signal sequence such as logarithmic approximate companding PCM. The companding means that the magnitude relationship of the original signal sequence is indicated by a number series. Further, the number series indicating the magnitude relationship of the original signal sequence is a number given at equal intervals while maintaining the magnitude relationship or by inverting the magnitude relationship. FIG. 1 is a diagram illustrating an example of the amplitude of the second signal sequence. The horizontal axis is a value in the case of linear PCM, and the vertical axis is a corresponding value in the case of logarithmic approximate companding PCM. FIG. 2 is a diagram showing a specific form of the 8-bit μ-rule. It consists of 1 bit (polarity) indicating positive / negative, 3 bits (exponent part) indicating exponent, and 4 bits (linear part) indicating increment (slope) with a linear sign. In the case of this type of logarithmic approximate companding PCM, numerical values from −127 to 127 can be expressed. This corresponds to linear PCM from -8158 to 8158 (FIG. 1).

対数近似圧伸ＰＣＭなどの圧伸された信号列（以下、「第２信号列」という）を圧縮符号化する技術として、以下のような符号化装置と復号化装置が考えられる。図３に、第２信号列を符号化する符号化装置の機能構成例を示す。また、図４に、この符号化装置の処理フロー例を示す。符号化装置８００は、線形予測部８１０、量子化部８２０、予測値算出部８３０、減算部８４０、係数符号化部８５０、残差符号化部８６０を備える。さらに、符号化装置８００への入力信号列がフレーム単位に分割されていない場合は、符号化装置８００は、フレーム分割部８７０も備えている。フレーム分割部８７０は、入力信号列をフレーム単位に分割した第２信号列Ｘ＝｛ｘ（１），ｘ（２），…，ｘ（Ｎ）｝を出力する。なお、Ｎは１フレームのサンプル数である。   The following encoding apparatus and decoding apparatus are conceivable as techniques for compressing and encoding a companded signal sequence such as logarithmic approximate companding PCM (hereinafter referred to as “second signal sequence”). FIG. 3 shows a functional configuration example of an encoding device that encodes the second signal sequence. FIG. 4 shows an example of the processing flow of this encoding apparatus. The encoding apparatus 800 includes a linear prediction unit 810, a quantization unit 820, a predicted value calculation unit 830, a subtraction unit 840, a coefficient encoding unit 850, and a residual encoding unit 860. Furthermore, when the input signal sequence to the encoding apparatus 800 is not divided into frames, the encoding apparatus 800 also includes a frame dividing unit 870. The frame dividing unit 870 outputs a second signal sequence X = {x (1), x (2),..., X (N)} obtained by dividing the input signal sequence into frames. N is the number of samples in one frame.

符号化装置８００に、フレーム単位に分割された第２信号列Ｘが入力されると、線形予測部８１０は、フレーム単位に分割された第２信号列Ｘから線形予測係数Ｋ＝｛ｋ（１），ｋ（２），…，ｋ（Ｐ）｝を求める（Ｓ８１０）。なお、Ｐは予測次数である。量子化部８２０は、線形予測係数Ｋを量子化して量子化線形予測係数Ｋ’＝｛ｋ’（１），ｋ’（２），…，ｋ’（Ｐ）｝を求める（Ｓ８２０）。予測値算出部８３０は、第２信号列Ｘと量子化線形予測係数Ｋ’を用いて、次式のように第２予測値列Ｙ＝｛ｙ（１），ｙ（２），…，ｙ（Ｎ）｝を求める（Ｓ８３０）。

Figure 0005006774
ただし、ｎは１以上Ｎ以下の整数である。減算部８４０は、第２信号列Ｘと第２予測値列Ｙとの差（予測残差列）Ｅ＝｛ｅ（１），ｅ（２），…，ｅ（Ｎ）｝を求める（Ｓ８４０）。係数符号化部８５０は、量子化線形予測係数Ｋ’を符号化し、予測係数符号Ｃｋを出力する（Ｓ８５０）。残差符号化部８６０は、予測残差列Ｅを符号化し、予測残差符号Ｃｅを出力する（Ｓ８６０）。 When the second signal sequence X divided into frames is input to the encoding apparatus 800, the linear prediction unit 810 calculates the linear prediction coefficient K = {k (1) from the second signal sequence X divided into frames. ), K (2),..., K (P)} are obtained (S810). Note that P is the predicted order. The quantization unit 820 quantizes the linear prediction coefficient K to obtain a quantized linear prediction coefficient K ′ = {k ′ (1), k ′ (2),..., K ′ (P)} (S820). The predicted value calculation unit 830 uses the second signal sequence X and the quantized linear prediction coefficient K ′ to generate a second predicted value sequence Y = {y (1), y (2),. (N)} is obtained (S830).
Figure 0005006774
 However, n is an integer of 1 or more and N or less. The subtraction unit 840 obtains a difference (prediction residual sequence) E = {e (1), e (2),..., E (N)} between the second signal sequence X and the second predicted value sequence Y (S840). ). The coefficient encoding unit 850 encodes the quantized linear prediction coefficient K ′ and outputs a prediction coefficient code C k (S850). Residual coding unit 860 encodes the prediction residual sequence E, and outputs a prediction residual code C e (S860).

図５に、第２信号列に復号化する復号化装置の機能構成例を示す。また、図６に、この復号化装置の処理フロー例を示す。復号化装置９００は、残差復号化部９１０、係数復号化部９２０、予測値算出部９３０、加算部９４０を備える。残差復号化部９１０は、予測残差符号Ｃｅと復号化して予測残差列Ｅを求める（Ｓ９１０）。係数復号化部９２０は、予測係数符号Ｃｋを復号化して量子化線形予測係数Ｋ’を求める（Ｓ９２０）。予測値算出部９３０は、復号化された第２信号列Ｘと量子化線形予測係数Ｋ’を用いて、次式のように第２予測値列Ｙを求める（Ｓ９３０）。

Figure 0005006774
加算部９４０は、第２予測値列Ｙと予測残差列Ｅとを加算して第２信号列Ｘを求める（Ｓ９４０）。このような構成により、圧伸された信号列を可逆圧縮できる。しかし、Ｇ．７１１などの圧伸された信号列を、上述のように可逆圧縮しても圧縮効率が十分高いとは言えない。 FIG. 5 shows an example of a functional configuration of a decoding device that decodes the second signal sequence. FIG. 6 shows an example of the processing flow of this decoding apparatus. The decoding apparatus 900 includes a residual decoding unit 910, a coefficient decoding unit 920, a predicted value calculation unit 930, and an addition unit 940. Residual decoding unit 910 obtains a prediction residual sequence E decodes the prediction residual code C e (S910). The coefficient decoding unit 920 decodes the prediction coefficient code C k to obtain a quantized linear prediction coefficient K ′ (S920). The predicted value calculation unit 930 obtains the second predicted value sequence Y using the decoded second signal sequence X and the quantized linear prediction coefficient K ′ as in the following equation (S930).
Figure 0005006774
 The adder 940 adds the second predicted value sequence Y and the predicted residual sequence E to obtain the second signal sequence X (S940). With such a configuration, the stretched signal sequence can be reversibly compressed. However, G. Even if the compressed signal sequence such as 711 is reversibly compressed as described above, it cannot be said that the compression efficiency is sufficiently high.

本発明は、このような状況に鑑みてなされたものであり、圧伸された信号列に対して高い符号化効率を実現し、符号量を削減することを目的とする。   The present invention has been made in view of such a situation, and an object of the present invention is to realize high coding efficiency and reduce the amount of codes with respect to a companded signal sequence.

本発明の符号化方法は、元の信号列の大小関係を示す番号系列（以下、「第２信号列」という）を符号化する符号化方法であって、線形予測ステップ、量子化ステップ、算出用対応変換候補出力ステップ、予測値算出ステップ、減算ステップ、係数符号化ステップ、残差符号化ステップ、最適選定ステップを有する。なお、「元の信号列の大小関係を示す番号系列」とは、大小関係を維持したまま、あるいは大小関係を反転して、均等間隔に付された数である。例えば、１，２，３，…でもよいし、２，４，６，…のようにしてもよい。   The encoding method of the present invention is an encoding method for encoding a number sequence (hereinafter referred to as “second signal sequence”) indicating the magnitude relationship of the original signal sequence, and includes a linear prediction step, a quantization step, and a calculation. A corresponding conversion candidate output step, a predicted value calculation step, a subtraction step, a coefficient encoding step, a residual encoding step, and an optimum selection step. The “number sequence indicating the magnitude relationship of the original signal sequence” is a number given at equal intervals while maintaining the magnitude relationship or by inverting the magnitude relationship. For example, 1, 2, 3,..., 2, 4, 6,.

線形予測ステップは、第２信号列を用いて、線形予測係数を求める。量子化ステップは、線形予測係数を量子化して量子化線形予測係数を求める。算出用対応変換候補出力ステップは、元の信号列と線形な関係に近づける可逆な処理である算出用対応変換の候補を、あらかじめ定めた手順で出力する。なお、「元の信号列と線形な関係に近づける処理」には、元の信号列と線形な関係の信号列にする処理は含まない。予測値算出ステップは、算出用対応変換の候補ごとに、第２信号列と量子化線形予測係数を用いて、予測値列の振幅を圧縮した第２予測値列を求める。減算ステップは、算出用対応変換の候補ごとに、第２信号列と第２予測値列との差を求め、予測残差列を求める。係数符号化ステップは、量子化線形予測係数を符号化し、予測係数符号を出力する。残差符号化ステップは、予測残差列を符号化し、予測残差符号を出力する。最適選定ステップは、あらかじめ定めた条件を満たすまで実行された繰返しの間に算出用対応変換候補出力ステップが出力した複数の算出用対応変換の候補の中から、予測残差列から求めた符号量の推定値を最小にする算出用対応変換を選び、選ばれた算出用対応変換を特定する処理情報と当該算出用対応変換を用いた時の予測残差列を出力する。なお、予測残差列の各信号の絶対値の和や、各信号の２乗の和などを求めることにより符号量を推定できる。または、最適選定ステップは、あらかじめ定めた条件を満たすまで実行された繰返しの間に算出用対応変換候補出力ステップが出力した複数の算出用対応変換の候補の中から、予測係数符号と予測残差符号を合わせた符号量を最小にする算出用対応変換を選び、選ばれた算出用対応変換を特定する処理情報と当該算出用対応変換を用いた時の予測残差符号を出力する。   In the linear prediction step, a linear prediction coefficient is obtained using the second signal sequence. In the quantization step, the linear prediction coefficient is quantized to obtain a quantized linear prediction coefficient. The calculation correspondence conversion candidate output step outputs a calculation correspondence conversion candidate, which is a reversible process that approximates a linear relationship with the original signal sequence, according to a predetermined procedure. It should be noted that “a process for bringing a linear relationship with an original signal sequence” does not include a process for making a signal sequence with a linear relationship with the original signal sequence. The predicted value calculation step obtains a second predicted value sequence obtained by compressing the amplitude of the predicted value sequence using the second signal sequence and the quantized linear prediction coefficient for each candidate for conversion for calculation. In the subtraction step, a difference between the second signal sequence and the second predicted value sequence is obtained for each candidate for conversion for calculation, and a predicted residual sequence is obtained. The coefficient encoding step encodes the quantized linear prediction coefficient and outputs a prediction coefficient code. The residual encoding step encodes the prediction residual sequence and outputs a prediction residual code. The optimal selection step includes a code amount obtained from a prediction residual sequence from among a plurality of calculation corresponding conversion candidates output by the calculation corresponding conversion candidate output step during iterations executed until a predetermined condition is satisfied. The calculation corresponding conversion for minimizing the estimated value is selected, and processing information for specifying the selected calculation corresponding conversion and a prediction residual sequence when using the calculation corresponding conversion are output. Note that the code amount can be estimated by obtaining the sum of absolute values of each signal of the prediction residual sequence, the sum of squares of each signal, and the like. Alternatively, the optimal selection step may include a prediction coefficient code and a prediction residual from among a plurality of calculation corresponding conversion candidates output by the calculation corresponding conversion candidate output step that are executed until a predetermined condition is satisfied. The calculation correspondence conversion that minimizes the code amount combined with the code is selected, and the processing information for specifying the selected calculation correspondence conversion and the prediction residual code when using the calculation correspondence conversion are output.

また、予測値算出ステップは、算出用線形対応サブステップ、算出サブステップ、第２予測サブステップを有する。算出用線形対応サブステップは、第２信号列を、算出用対応変換の候補を用いて算出用信号列に変換する。算出サブステップは、算出用信号列と量子化線形予測係数を用いて予測値列を求める。第２予測サブステップは、算出用線形対応サブステップの逆の処理によって、予測値列の振幅を圧縮して第２予測値列を求める。   The predicted value calculation step includes a calculation linear correspondence substep, a calculation substep, and a second prediction substep. The calculation linear correspondence sub-step converts the second signal sequence into a calculation signal sequence using a calculation correspondence conversion candidate. In the calculation sub-step, a predicted value sequence is obtained using the calculation signal sequence and the quantized linear prediction coefficient. In the second prediction sub-step, the second predicted value sequence is obtained by compressing the amplitude of the predicted value sequence by the reverse process of the calculation linear correspondence sub-step.

算出用対応変換の候補をあらかじめ定めた手順で決める方法として、例えば、算出用対応変換候補出力ステップは、元の信号列を線形な関係に近づける可逆な処理を、あらかじめ定めた複数の算出用対応変換の候補の中から１つずつ選ぶ方法がある。この場合、最適選定ステップのあらかじめ定めた条件を満たすまで実行された繰返しとは、全ての算出用対応変換の候補が選ばれたことである。したがって、最適選定ステップは、複数の算出用対応変換の候補の中から、予測残差列から求めた符号量の推定値を最小にする算出用対応変換を選び、選ばれた算出用対応変換の処理情報と当該算出用対応変換を用いた時の予測残差列を出力すればよい。あるいは、最適選定ステップは、複数の算出用対応変換の候補の中から、予測係数符号と予測残差符号を合わせた符号量を最小にする算出用対応変換を選び、選ばれた算出用対応変換の処理情報と当該算出用対応変換を用いた時の予測残差符号を出力すればよい。つまり、どのような方法を用いるかに関わらず、最終的に符号量が最小になる算出用対応変換を求めればよく、その算出用対応変換を特定する情報を出力できればよい。   As a method for determining candidates for conversion corresponding to calculation in a predetermined procedure, for example, the calculation conversion conversion candidate output step includes a plurality of predetermined calculation correspondences corresponding to a reversible process that brings the original signal sequence closer to a linear relationship. There is a method of selecting one by one from conversion candidates. In this case, the repetition that is executed until the predetermined condition of the optimum selection step is satisfied means that all the candidates for conversion for calculation are selected. Therefore, the optimum selection step selects a calculation correspondence conversion that minimizes the estimated value of the code amount obtained from the prediction residual sequence from a plurality of calculation correspondence conversion candidates, and selects the selected calculation correspondence conversion. What is necessary is just to output the prediction residual sequence when the processing information and the corresponding conversion for calculation are used. Alternatively, the optimal selection step selects a calculation conversion conversion that minimizes the code amount of the prediction coefficient code and the prediction residual code from among a plurality of calculation conversion conversion candidates, and the selected calculation conversion conversion And the prediction residual code when the corresponding conversion for calculation is used. That is, regardless of what method is used, it is only necessary to obtain a calculation correspondence conversion that finally minimizes the code amount, and it is only necessary to output information specifying the calculation correspondence conversion.

また、算出用対応変換候補出力ステップで出力する算出用対応変換の候補は、第２信号列と、元の信号列と線形な信号列との重みつき加算とすればよい。この場合には、処理情報を、重みつき加算の重み情報とすればよい。
なお、線形予測ステップは、分析用線形対応サブステップと分析係数サブステップとを有してもよい。この場合、分析用線形対応サブステップは、第２信号列を、元の信号列と線形な関係に近づける処理によって分析用信号列に変換する。分析係数サブステップは、分析用信号列を線形予測分析して線形予測係数を求める。 The calculation correspondence conversion candidate output in the calculation correspondence conversion candidate output step may be a weighted addition of the second signal sequence, the original signal sequence, and the linear signal sequence. In this case, the processing information may be weighted information for weighted addition.
Note that the linear prediction step may include an analysis linear correspondence substep and an analysis coefficient substep. In this case, the analysis linear correspondence sub-step converts the second signal sequence into an analysis signal sequence by a process of bringing the second signal sequence closer to a linear relationship with the original signal sequence. In the analysis coefficient sub-step, a linear prediction coefficient is obtained by performing linear prediction analysis on the signal sequence for analysis.

本発明の復号化方法は、元の信号列の大小関係を示す番号系列（以下、「第２信号列」という）に復号化する方法であって、残差復号化ステップ、係数復号化ステップ、予測値算出ステップ、加算ステップを有する。残差復号化ステップは、予測残差符号から予測残差列を求める。係数復号化ステップは、予測係数符号から量子化線形予測係数を求める。予測値算出ステップは、第２信号列を元の信号列と線形な関係に近づける可逆な処理を特定するための処理情報と、復号化された第２信号列と、量子化線形予測係数を用いて、予測値列の振幅を圧縮した第２予測値列を求める。加算ステップは、第２予測値列と予測残差列とを加算して第２信号列を求める。予測値算出ステップは、復号線形対応サブステップ、復号予測サブステップ、第２復号サブステップを有する。復号線形対応サブステップは、復号化された第２信号列を、処理情報によって特定された元の信号列と線形な関係に近づける可逆な処理によって、算出用信号列に変換する。復号予測サブステップは、算出用信号列と量子化線形予測係数を用いて予測値列を求める。第２復号サブステップは、復号線形対応サブステップの逆の処理によって、予測値列の振幅を圧縮して第２予測値列を求める。   The decoding method of the present invention is a method of decoding into a number sequence (hereinafter referred to as “second signal sequence”) indicating the magnitude relationship of the original signal sequence, including a residual decoding step, a coefficient decoding step, It has a predicted value calculation step and an addition step. In the residual decoding step, a prediction residual sequence is obtained from the prediction residual code. In the coefficient decoding step, a quantized linear prediction coefficient is obtained from the prediction coefficient code. The predicted value calculation step uses processing information for specifying a reversible process for bringing the second signal sequence closer to a linear relationship with the original signal sequence, the decoded second signal sequence, and the quantized linear prediction coefficient. Thus, a second predicted value sequence in which the amplitude of the predicted value sequence is compressed is obtained. The adding step adds the second predicted value sequence and the predicted residual sequence to obtain a second signal sequence. The predicted value calculation step includes a decoded linear correspondence substep, a decoded prediction substep, and a second decoding substep. The decoding linear correspondence sub-step converts the decoded second signal sequence into a calculation signal sequence by a reversible process that approximates a linear relationship with the original signal sequence specified by the processing information. In the decoding prediction sub-step, a prediction value sequence is obtained using the calculation signal sequence and the quantized linear prediction coefficient. The second decoding sub-step obtains the second predicted value sequence by compressing the amplitude of the predicted value sequence by the reverse process of the decoding linear correspondence sub-step.

また、復号線形対応サブステップの処理は、第２信号列と、元の信号列と線形な信号列との重みつき加算とすればよい。この場合、処理情報は、重みつき加算の重み情報とすればよい。   The decoding linear correspondence sub-step process may be a weighted addition of the second signal sequence, the original signal sequence, and the linear signal sequence. In this case, the processing information may be weight information for weighted addition.

一般的に、線形な信号列は効率よく予測できる。しかし、線形な信号列は、もともと振幅を表すためのビット数が多くなるので符号量も多くなってしまう。一方、圧伸された信号列をそのまま数値とみなせば、振幅を表すためのビット数を少なくできる。しかし、波形自体が不自然になってしまうので、予測効率が悪くなる。本発明の符号化方法と復号化方法によれば、予測値列の算出（予測値算出ステップ）に用いる信号列として、第２信号列よりも元の信号列と線形な関係に近い信号列の中で符号化効率のよい信号列を探索して用いるので、予測残差列から求めた符号量の推定値を小さくでき、符号化の効率を高めることができる。また、その結果として符号量を少なくできる。   In general, a linear signal sequence can be predicted efficiently. However, since the linear signal sequence originally has a large number of bits for representing the amplitude, the code amount also increases. On the other hand, if the companded signal sequence is regarded as a numerical value as it is, the number of bits for representing the amplitude can be reduced. However, since the waveform itself becomes unnatural, prediction efficiency deteriorates. According to the encoding method and the decoding method of the present invention, a signal sequence used for calculation of a predicted value sequence (predicted value calculation step) is a signal sequence closer to a linear relationship with the original signal sequence than the second signal sequence. Since a signal sequence having good coding efficiency is searched for and used, the estimated value of the code amount obtained from the prediction residual sequence can be reduced, and the coding efficiency can be increased. As a result, the code amount can be reduced.

以下では、説明の重複を避けるため同じ機能を有する構成部や同じ処理を行う処理ステップには同一の番号を付与し、説明を省略する。
［第１実施形態］
図７に、第１実施形態の圧伸された信号列（第２信号列）を符号化する符号化装置の機能構成例を示す。また、図８に、この符号化装置の処理フロー例を示す。符号化装置１００は、符号化装置８００（図３）と予測値算出部１３０、算出用対応変換候補出力部１７０、最適選定部１８０が異なる。その他の構成は同じである。 Below, in order to avoid duplication of description, the same number is given to the structural part which has the same function, and the process step which performs the same process, and description is abbreviate | omitted.
[First Embodiment]
FIG. 7 illustrates a functional configuration example of an encoding device that encodes the deflated signal sequence (second signal sequence) according to the first embodiment. FIG. 8 shows an example of the processing flow of this encoding apparatus. The encoding apparatus 100 is different from the encoding apparatus 800 (FIG. 3) in a predicted value calculation unit 130, a corresponding conversion candidate output unit for calculation 170, and an optimum selection unit 180. Other configurations are the same.

算出用対応変換候補出力部１７０は、第２信号列Ｘ＝｛ｘ（１），ｘ（２），…，ｘ（Ｎ）｝を、元の信号列と線形な関係に近づける可逆な処理である算出用対応変換の候補Ｆ（）を、あらかじめ定めた手順で出力する（Ｓ１７０）。算出用対応変換の候補をあらかじめ定めた手順で決める方法として、例えば、元の信号列を線形な関係に近づける可逆な処理を、あらかじめ定めた複数の算出用対応変換の候補の中から１つずつ選ぶ方法がある。あるいは、予測残差列から求めた符号量の推定値が減る方向に算出用対応変換の候補Ｆ（）を調整していく方法などがある。なお、予測残差列の各信号の絶対値の和や、各信号の２乗の和などを求めることにより、予測残差列から符号量を推定できる。   The calculation corresponding conversion candidate output unit 170 is a reversible process that brings the second signal sequence X = {x (1), x (2),..., X (N)} into a linear relationship with the original signal sequence. A calculation conversion candidate F () is output in a predetermined procedure (S170). As a method for deciding the candidate for conversion for calculation in a predetermined procedure, for example, a reversible process for bringing the original signal sequence close to a linear relationship is performed one by one from a plurality of predetermined candidates for conversion for calculation. There is a way to choose. Alternatively, there is a method of adjusting the calculation conversion candidate F () in a direction in which the estimated code amount obtained from the prediction residual sequence decreases. Note that the code amount can be estimated from the prediction residual sequence by obtaining the sum of absolute values of the signals of the prediction residual sequence, the sum of squares of the signals, and the like.

予測値算出部１３０は、算出用線形対応手段１３１、算出手段１３２、第２予測手段１３３を有する。算出用線形対応手段１３１は、第２信号列Ｘを、算出用対応変換の候補Ｆ（）によって、算出用信号列Ｆ（Ｘ）に変換する（Ｓ１３１）。算出手段１３２は、算出用信号列Ｆ（Ｘ）と量子化線形予測係数Ｋ’を用いて、次式のように予測値列Ｆ（Ｙ）＝｛Ｆ（ｙ（１）），Ｆ（ｙ（２）），…，Ｆ（ｙ（Ｎ））｝を求める（Ｓ１３２）。

Figure 0005006774
ただし、ｎは１以上Ｎ以下の整数である。第２予測手段１３３は、ステップＳ１３１の逆の処理Ｆ−１（）によって、予測値列Ｆ（Ｙ）の振幅を圧縮して第２予測値列Ｙ＝｛ｙ（１），ｙ（２），…，ｙ（Ｎ）｝を求める（Ｓ１３３）。 The predicted value calculation unit 130 includes a calculation linear correspondence unit 131, a calculation unit 132, and a second prediction unit 133. The calculation linear correspondence unit 131 converts the second signal sequence X into the calculation signal sequence F (X) using the calculation correspondence conversion candidate F () (S131). The calculation means 132 uses the calculation signal sequence F (X) and the quantized linear prediction coefficient K ′ to calculate the prediction value sequence F (Y) = {F (y (1)), F (y (2)),..., F (y (N))} is obtained (S132).
Figure 0005006774
 However, n is an integer of 1 or more and N or less. The second prediction means 133 compresses the amplitude of the predicted value sequence F (Y) by the reverse process F −1 () of step S131, and the second predicted value sequence Y = {y (1), y (2). ,..., Y (N)} are obtained (S133).

なお、圧伸とは、元の信号列の大小関係を番号系列で示すことを意味している。また、元の信号列の大小関係を示す番号系列とは、大小関係を維持したまま、あるいは大小関係を反転して、均等間隔に付された数である。非特許文献２（Ｇ．７１１）には、Ａ則やμ則の場合の具体例が表で示されている（非特許文献２のＴａｂｌｅ １ａ〜２ｂ）。Ａ則の場合もμ則の場合も、非特許文献２の表の第６列に「８ビットの形式（図２参照）」、第７列に「元の信号の量子化値」、第８列に「元の信号の大小関係を示す番号」が示されている。「８ビットの形式」は、０と１とを反転させるなどのビット形式を決めるルールに従って定められている。これを、ビット形式を決めるルールに従って数値に戻したものが、「元の信号の大小関係を示す番号」である。非特許文献２の「元の信号の大小関係を示す番号」が、本発明の第２信号列の１つのサンプル値に相当する。また、非特許文献２の「元の信号の量子化値」が、元の信号列と線形な関係の信号列の１つのサンプル値に相当する。例えば、μ則の“１１１０１１１１”という８ビットは、元の信号の大小関係を示す番号は１６であり、元の信号の量子化値は３３である。また、μ則の“１０００１１１１”という８ビットは、元の信号の大小関係を示す番号は１１２であり、元の信号の量子化値は４１９１である。   The companding means that the magnitude relationship of the original signal sequence is indicated by a number series. Further, the number series indicating the magnitude relationship of the original signal sequence is a number given at equal intervals while maintaining the magnitude relationship or by inverting the magnitude relationship. Non-Patent Document 2 (G.711) shows a table of specific examples in the case of A-law and μ-law (Tables 1a to 2b of Non-Patent Document 2). In the case of the A-law and the μ-law, the sixth column of the table of Non-Patent Document 2 is “8-bit format (see FIG. 2)”, the seventh column is “the quantized value of the original signal”, the eighth In the column, “number indicating the magnitude relation of the original signal” is shown. The “8-bit format” is defined according to a rule that determines a bit format, such as inverting 0 and 1. This is a “number indicating the magnitude relationship of the original signal” that is converted back to a numerical value in accordance with the rule for determining the bit format. The “number indicating the magnitude relationship of the original signals” in Non-Patent Document 2 corresponds to one sample value of the second signal sequence of the present invention. Further, the “quantized value of the original signal” in Non-Patent Document 2 corresponds to one sample value of a signal sequence having a linear relationship with the original signal sequence. For example, in the 8 bits of “11101111” in the μ rule, the number indicating the magnitude relation of the original signal is 16, and the quantized value of the original signal is 33. In addition, the 8 bits of “10001111” in the μ rule have a number 112 indicating the magnitude relation of the original signal, and the quantized value of the original signal is 4191.

符号化装置１００は、あらかじめ定めた繰返しの条件を満たすかを確認する（Ｓ１７５）。あらかじめ定めた繰返しの条件は、算出用対応変換の候補を選ぶ手順が、あらかじめ定めた算出用対応変換の候補から順次選ぶ場合には、あらかじめ定めた算出用対応変換の候補の全てに対してステップＳ１７０、Ｓ１３０、Ｓ８４０が終了したときとすればよい。また、算出用対応変換の候補を選ぶ手順が、予測残差列から求めた符号量の推定値が減る方向に算出用対応変換の候補Ｆ（）を調整していく場合には、予測誤差が閾値以下となったときとすればよい。   The encoding apparatus 100 confirms whether a predetermined repetition condition is satisfied (S175). If the procedure for selecting candidates for conversion for calculation is selected sequentially from predetermined candidates for conversion for calculation, the predetermined repetition condition is a step for all of the candidates for conversion corresponding to calculation. It may be when S170, S130, and S840 are completed. Also, when the procedure for selecting a candidate for conversion for calculation adjusts the candidate for conversion for calculation F () in a direction in which the estimated value of the code amount obtained from the prediction residual sequence decreases, the prediction error is increased. What is necessary is just to become when it becomes below a threshold.

ステップＳ１７５が条件を満たさない場合には、ステップＳ１７０に戻り、算出用対応変換候補出力部１７０が、あらかじめ定めた手順で次の算出用対応変換の候補Ｆ（）を出力する。ステップＳ１７５が条件を満たす場合には、最適選定部１８０は、繰返し処理の間にステップＳ１７０（算出用対応変換候補出力ステップ）が出力した複数の算出用対応変換の候補の中から、予測残差列から求めた符号量の推定値を最小にする算出用対応変換を選び、選ばれた算出用対応変換を特定する処理情報Ｍと当該算出用対応変換Ｆ（）を用いた時の予測残差列Ｅを出力する（Ｓ１８０）。残差符号化部８６０は、最適選定部１８０が出力した予測残差列Ｅを符号化する（Ｓ８６０）。   If step S175 does not satisfy the condition, the process returns to step S170, and the calculation correspondence conversion candidate output unit 170 outputs the next calculation correspondence conversion candidate F () according to a predetermined procedure. If step S175 satisfies the condition, the optimum selection unit 180 selects a prediction residual from the plurality of calculation correspondence conversion candidates output by step S170 (calculation correspondence conversion candidate output step) during the iterative process. A calculation residual conversion that minimizes the estimated value of the code amount obtained from the column is selected, and a prediction residual when using the processing information M for specifying the selected calculation correspondence conversion and the calculation correspondence conversion F () is used. The column E is output (S180). The residual encoding unit 860 encodes the prediction residual sequence E output from the optimal selection unit 180 (S860).

図９に、第１実施形態の第２信号列に復号化する復号化装置の機能構成例を示す。また、図１０に、この復号化装置の処理フロー例を示す。復号化装置３００は、予測残差符号Ｃｅ、予測係数符号Ｃｋ、処理情報Ｍを入力とし、第２信号列Ｘを出力とする。復号化装置３００は、復号化装置９００（図５）と予測値算出部３３０が異なり、その他の構成は同じである。予測値算出部３３０は、復号線形対応手段３３１、復号予測手段３３２、第２復号手段３３３を有する。復号線形対応手段３３１は、復号化された第２信号列Ｘを、処理情報Ｍによって特定された元の信号列と線形な関係に近づける可逆な処理Ｆ（）によって、算出用信号列Ｆ（Ｘ）に変換する（Ｓ３３１）。復号予測手段３３２は、算出用信号列Ｆ（Ｘ）と量子化線形予測係数Ｋ’を用いて、次式のように予測値列Ｆ（Ｙ）を求める（Ｓ３３２）。

Figure 0005006774
第２復号手段３３３は、ステップＳ３３１の逆の処理Ｆ−１（）によって、予測値列Ｆ（Ｙ）の振幅を圧縮して第２予測値列Ｙを求める（Ｓ３３３）。 FIG. 9 shows an example of a functional configuration of a decoding apparatus that decodes the second signal sequence according to the first embodiment. FIG. 10 shows an example of the processing flow of this decoding apparatus. The decoding apparatus 300 receives the prediction residual code C e , the prediction coefficient code C k , and the processing information M, and outputs the second signal sequence X. The decoding apparatus 300 differs from the decoding apparatus 900 (FIG. 5) in the predicted value calculation unit 330, and the other configurations are the same. The predicted value calculation unit 330 includes decoded linear correspondence means 331, decoded prediction means 332, and second decoding means 333. The decoding linear correspondence unit 331 performs the calculation signal sequence F (X) by the reversible processing F () that brings the decoded second signal sequence X into a linear relationship with the original signal sequence specified by the processing information M. (S331). The decoding prediction unit 332 uses the calculation signal sequence F (X) and the quantized linear prediction coefficient K ′ to obtain the prediction value sequence F (Y) as in the following equation (S332).
Figure 0005006774
 The second decoding means 333 obtains the second predicted value sequence Y by compressing the amplitude of the predicted value sequence F (Y) by the reverse process F −1 () of step S331 (S333).

符号化装置１００のステップＳ１３１（算出用線形対応サブステップ）、復号化装置３００のステップＳ３３１（復号線形対応サブステップ）で行われる「第２信号列Ｘを、元の信号列と線形な関係に近づける処理（算出用対応変換）Ｆ（）」とは、圧伸された信号列と元の信号列と線形な関係の信号列との中間的な信号列にする処理であり、元の信号列と線形な関係の信号列にする処理は含まない。具体的には、以下のような処理である。線形な関係とは、元の信号列の１つのサンプル値の振幅をｓとするときに、
｜１−Ｈ（αｓ）／αＨ（ｓ）｜≒０
ただし、αは任意の実数
を満足する関数Ｈ（）によって変換された信号列を意味している。なお、この式では離散化に伴う誤差は無視している。第２信号列の１つのサンプル値の振幅ｘと元の信号列の１つのサンプル値の振幅ｓとの関係がｘ＝Ｇ（ｓ）の場合は、任意のαに対しては
｜１−Ｇ（αｓ）／αＧ（ｓ）｜≒０
を満足しない。「線形な関係に近づける処理（算出用対応変換）」とは、この処理を関数Ｆ（）とすると、任意のαに対して、
｜１−Ｆ（αｘ）／αＦ（ｘ）｜＜｜１−Ｇ（αｓ）／αＧ（ｓ）｜
となり、かつ、すべてのαに対しては
｜１−Ｆ（αｘ）／αＦ（ｘ）｜≒０
は満足しない。たとえば、第２信号列の１つのサンプル値の振幅ｘと元の信号列の１つのサンプル値の振幅ｓとの重みつき加算（たとえば、ｇを重みとしてｘ＋ｇｓ）を行う処理がある。また、算出用対応変換Ｆ（）は符号化装置と復号化装置とで同じにする必要がある。上記の重み付加算の方法の場合、重みｇまたは重みｇを示す符号を処理情報Ｍとすれば、処理情報Ｍによって算出用対応変換Ｆ（）が特定できる。したがって、符号化装置と復号化装置とで同じ処理が行えるし、逆の処理Ｆ−１（）も容易に実行できる。 “The second signal sequence X is linearly related to the original signal sequence, which is performed in step S131 (calculation linear correspondence substep) of the encoding device 100 and in step S331 (decoding linear correspondence substep) of the decoding device 300. The process of approaching (corresponding conversion for calculation) F () ”is a process of making an intermediate signal sequence between the companded signal sequence and the signal sequence in a linear relationship with the original signal sequence. It does not include processing to make a signal sequence linearly related to Specifically, the processing is as follows. The linear relationship means that when the amplitude of one sample value of the original signal sequence is s,
| 1-H (αs) / αH (s) | ≈0
Here, α means a signal sequence converted by a function H () satisfying an arbitrary real number. In this equation, errors due to discretization are ignored. When the relationship between the amplitude x of one sample value of the second signal sequence and the amplitude s of one sample value of the original signal sequence is x = G (s), for any α, | 1-G (Αs) / αG (s) | ≈0
Not satisfied. “Processing that approximates a linear relationship (corresponding conversion for calculation)” is a function F ().
| 1-F (αx) / αF (x) | <| 1-G (αs) / αG (s) |
And for all αs, | 1-F (αx) / αF (x) | ≈0
Is not satisfied. For example, there is a process of performing a weighted addition (for example, x + gs with g as a weight) between the amplitude x of one sample value of the second signal sequence and the amplitude s of one sample value of the original signal sequence. Also, the calculation corresponding transform F () needs to be the same in the encoding device and the decoding device. In the case of the above weighted addition method, if the weight g or a code indicating the weight g is the processing information M, the calculation corresponding conversion F () can be specified by the processing information M. Therefore, the same processing can be performed by the encoding device and the decoding device, and the reverse processing F −1 () can be easily executed.

本実施形態の符号化装置と復号化装置によれば、予測値列の算出（予測値算出ステップ）に用いる信号列として、第２信号列よりも元の信号列と線形な関係に近い信号列の中で符号化効率のよい信号列を探索して用いる。したがって、予測残差列から求めた符号量の推定値を小さくでき、符号化の効率を高めることができる。また、その結果として符号量を少なくできる。   According to the encoding device and the decoding device of the present embodiment, a signal sequence that is closer to a linear relationship with the original signal sequence than the second signal sequence, as a signal sequence used for calculation of a predicted value sequence (predicted value calculation step). Among them, a signal sequence with good coding efficiency is searched and used. Therefore, the estimated value of the code amount obtained from the prediction residual sequence can be reduced, and the encoding efficiency can be increased. As a result, the code amount can be reduced.

［変形例］
図１１に、第１実施形態変形例の第２信号列を符号化する符号化装置の機能構成例を示す。また、図１２に、この符号化装置の処理フロー例を示す。符号化装置２００は、符号化装置１００（図７）と線形予測部２１０が異なる。その他の構成は同じである。線形予測部２１０は、分析用線形対応手段２１１と分析係数手段２１２とを有する。分析用線形対応手段２１１は、第２信号列Ｘを、元の信号列と線形な関係に近づける処理Ｆ’（）によって分析用信号列Ｆ’（Ｘ）に変換する（Ｓ２１１）。分析係数手段２１２は、分析用信号列Ｆ’（Ｘ）を線形予測分析して線形予測係数Ｋを求める（Ｓ２１２）。処理Ｆ’（）は線形予測係数Ｋを求めるために行う処理であり、その結果は線形予測係数Ｋに反映されるので、復号化装置には必要がなく、可逆である必要もない。したがって、適宜変更してもよい。 [Modification]
FIG. 11 illustrates a functional configuration example of an encoding device that encodes the second signal sequence according to the modification of the first embodiment. FIG. 12 shows an example of the processing flow of this encoding apparatus. The encoding device 200 is different from the encoding device 100 (FIG. 7) in the linear prediction unit 210. Other configurations are the same. The linear prediction unit 210 includes an analysis linear correspondence unit 211 and an analysis coefficient unit 212. The analysis linear correspondence unit 211 converts the second signal sequence X into an analysis signal sequence F ′ (X) by a process F ′ () that approximates a linear relationship with the original signal sequence (S211). The analysis coefficient means 212 performs linear prediction analysis on the analysis signal string F ′ (X) to obtain a linear prediction coefficient K (S212). The process F ′ () is a process performed for obtaining the linear prediction coefficient K, and the result is reflected in the linear prediction coefficient K. Therefore, the process F ′ () is not necessary for the decoding apparatus and does not need to be reversible. Therefore, you may change suitably.

本変形例の符号化装置によれば、圧伸された信号列を線形に近づけた上で線形予測係数を求めるので、さらに予測残差列から求めた符号量の推定値を小さくでき、符号化の効率を高めることができる。また、その結果として符号量を少なくできる。   According to the encoding device of the present modification, the linear prediction coefficient is obtained after making the expanded signal sequence close to linear, so that the estimated value of the code amount obtained from the prediction residual sequence can be further reduced. Can increase the efficiency. As a result, the code amount can be reduced.

［第２実施形態］
図１３に、第２実施形態の第２信号列を符号化する符号化装置の機能構成例を示す。また、図１４に、この符号化装置の処理フロー例を示す。符号化装置４００は、符号化装置１００（図７）と算出用対応変換候補出力部４７０、最適選定部４８０が異なる。その他の構成は同じである。 [Second Embodiment]
FIG. 13 illustrates a functional configuration example of an encoding device that encodes the second signal sequence according to the second embodiment. FIG. 14 shows an example of the processing flow of this encoding apparatus. The encoding apparatus 400 is different from the encoding apparatus 100 (FIG. 7) in the calculation corresponding conversion candidate output unit 470 and the optimum selection unit 480. Other configurations are the same.

算出用対応変換候補出力部４７０は、第２信号列Ｘ＝｛ｘ（１），ｘ（２），…，ｘ（Ｎ）｝を、元の信号列と線形な関係に近づける可逆な処理である算出用対応変換の候補Ｆ（）を、あらかじめ定めた手順で出力する（Ｓ４７０）。算出用対応変換の候補をあらかじめ定めた手順で決める方法として、例えば、元の信号列を線形な関係に近づける可逆な処理を、あらかじめ定めた複数の算出用対応変換の候補の中から１つずつ選ぶ方法がある。あるいは、予測係数符号と予測残差符号を合わせた符号量が減る方向に算出用対応変換の候補Ｆ（）を調整していく方法などがある。   The calculation corresponding conversion candidate output unit 470 is a reversible process that brings the second signal sequence X = {x (1), x (2),..., X (N)} into a linear relationship with the original signal sequence. A calculation conversion candidate F () is output in a predetermined procedure (S 470). As a method for deciding the candidate for conversion for calculation in a predetermined procedure, for example, a reversible process for bringing the original signal sequence close to a linear relationship is performed one by one from a plurality of predetermined candidates for conversion for calculation. There is a way to choose. Alternatively, there is a method of adjusting the calculation conversion candidate F () in a direction in which the code amount of the prediction coefficient code and the prediction residual code is reduced.

符号化装置４００は、あらかじめ定めた繰返しの条件を満たすかを確認する（Ｓ４７５）。あらかじめ定めた繰返しの条件は、算出用対応変換の候補を選ぶ手順が、あらかじめ定めた算出用対応変換の候補から順次選ぶ場合には、あらかじめ定めた算出用対応変換の候補の全てに対してステップＳ４７０、Ｓ１３０、Ｓ８４０、Ｓ８５０、Ｓ８６０が終了したときとすればよい。また、算出用対応変換の候補を選ぶ手順が、予測係数符号と予測残差符号を合わせた符号量が減る方向に算出用対応変換の候補Ｆ（）を調整していく場合には、符号量が閾値以下となったときとすればよい。   The encoding apparatus 400 confirms whether a predetermined repetition condition is satisfied (S475). If the procedure for selecting candidates for conversion for calculation is selected sequentially from predetermined candidates for conversion for calculation, the predetermined repetition condition is a step for all of the candidates for conversion corresponding to calculation. What is necessary is just to complete | finish S470, S130, S840, S850, and S860. In addition, when the procedure for selecting the candidate for conversion for calculation adjusts the candidate for conversion for calculation F () in a direction in which the code amount of the prediction coefficient code and the prediction residual code is reduced, the code amount May be when becomes less than or equal to the threshold.

ステップＳ４７５が条件を満たさない場合には、ステップＳ４７０に戻り、算出用対応変換候補出力部４７０が、あらかじめ定めた手順で次の算出用対応変換の候補Ｆ（）を出力する。ステップＳ４７５が、条件を満たす場合には、最適選定部４８０は、繰返し処理の間にステップＳ４７０（算出用対応変換候補出力ステップ）が出力した複数の算出用対応変換の候補の中から、符号量を最小にする算出用対応変換を選び、選ばれた算出用対応変換を特定する処理情報Ｍと当該算出用対応変換Ｆ（）を用いた時の予測残差符号Ｃｅを出力する（Ｓ４８０）。なお、ステップＳ４８０の処理に予測残差符号Ｃｅだけでなく予測係数符号Ｃｋも用いてもよいし、予測残差符号Ｃｅのみを用いてもよい。 If step S475 does not satisfy the condition, the process returns to step S470, and the calculation correspondence conversion candidate output unit 470 outputs the next calculation correspondence conversion candidate F () according to a predetermined procedure. If step S475 satisfies the condition, the optimum selection unit 480 selects the code amount from among a plurality of calculation correspondence conversion candidates output by step S470 (calculation correspondence conversion candidate output step) during the iterative processing. select a calculation corresponding conversion to minimize outputs the prediction residual code C e when using the processing information for specifying the corresponding conversion calculation selected M and the calculation for the corresponding conversion F () (S480) . Note that not only the prediction residual code C e but also the prediction coefficient code C k may be used in the process of step S480, or only the prediction residual code C e may be used.

第２実施形態の復号化装置は、第１実施形態（図９）と同じである。
第２実施形態の符号化装置と復号化装置によれば、第１実施形態と同じように、予測値列の算出（予測値算出ステップ）に用いる信号列として、第２信号列よりも元の信号列と線形な関係に近い信号列の中で符号化効率のよい信号列を探索して用いる。したがって、予測残差列から求めた符号量の推定値を小さくでき、符号化の効率を高めることができる。また、その結果として符号量を少なくできる。 The decoding device of the second embodiment is the same as that of the first embodiment (FIG. 9).
According to the encoding device and the decoding device of the second embodiment, as in the first embodiment, the signal sequence used for calculation of the predicted value sequence (predicted value calculation step) is more original than the second signal sequence. A signal sequence having good coding efficiency is searched for and used in a signal sequence having a linear relationship with the signal sequence. Therefore, the estimated value of the code amount obtained from the prediction residual sequence can be reduced, and the encoding efficiency can be increased. As a result, the code amount can be reduced.

［変形例］
図１５に、第２実施形態変形例の第２信号列を符号化する符号化装置の機能構成例を示す。また、図１６に、この符号化装置の処理フロー例を示す。符号化装置５００は、符号化装置４００（図１３）と線形予測部２１０が異なる。その他の構成は同じである。線形予測部２１０は、分析用線形対応手段２１１と分析係数手段２１２とを有する。分析用線形対応手段２１１は、第２信号列Ｘを、元の信号列と線形な関係に近づける処理Ｆ’（）によって分析用信号列Ｆ’（Ｘ）に変換する（Ｓ２１１）。分析係数手段２１２は、分析用信号列Ｆ’（Ｘ）を線形予測分析して線形予測係数Ｋを求める（Ｓ２１２）。処理Ｆ’（）は線形予測係数Ｋを求めるために行う処理であり、その結果は線形予測係数Ｋに反映されるので、復号化装置には必要がなく、可逆である必要もない。したがって、適宜変更してもよい。 [Modification]
FIG. 15 illustrates a functional configuration example of an encoding device that encodes the second signal sequence according to the modification of the second embodiment. FIG. 16 shows an example of the processing flow of this encoding apparatus. The encoding apparatus 500 is different from the encoding apparatus 400 (FIG. 13) in the linear prediction unit 210. Other configurations are the same. The linear prediction unit 210 includes an analysis linear correspondence unit 211 and an analysis coefficient unit 212. The analysis linear correspondence unit 211 converts the second signal sequence X into an analysis signal sequence F ′ (X) by a process F ′ () that approximates a linear relationship with the original signal sequence (S211). The analysis coefficient means 212 performs linear prediction analysis on the analysis signal string F ′ (X) to obtain a linear prediction coefficient K (S212). The process F ′ () is a process performed for obtaining the linear prediction coefficient K, and the result is reflected in the linear prediction coefficient K. Therefore, the process F ′ () is not necessary for the decoding apparatus and does not need to be reversible. Therefore, you may change suitably.

本変形例の符号化装置によれば、圧伸された信号列を線形に近づけた上で線形予測係数を求めるので、さらに予測残差列から求めた符号量の推定値を小さくでき、符号化の効率を高めることができる。また、その結果として符号量を少なくできる。
第１実施形態、第２実施形態に示したように、いくつかの方法で符号量を最小にする算出用対応変換を求めることができる。本発明の効果は、どのような方法で符号量を最小にする算出用対応変換を求めるかには関係ない。 According to the encoding device of the present modification, the linear prediction coefficient is obtained after making the expanded signal sequence close to linear, so that the estimated value of the code amount obtained from the prediction residual sequence can be further reduced. Can increase the efficiency. As a result, the code amount can be reduced.
As shown in the first embodiment and the second embodiment, the corresponding conversion for calculation that minimizes the code amount can be obtained by several methods. The effect of the present invention is irrelevant to the method for obtaining the corresponding conversion for calculation that minimizes the code amount.

［具体例］
図１７に、線形な関係に近づける処理Ｆ（）として第２信号列Ｘと元の信号列と線形な信号列Ｓ=｛ｓ（１），ｓ（２），…，ｓ（Ｎ）｝との重みつき加算（ｇを重みとしてＸｇ＋Ｓ）を行った場合の８ビットのμ則の形式（図２）の例を示す。なお、図１７では極性が正の場合のみを示している。また、μ則の指数部（セグメント）と線形部（レベル）は、一般的な感覚とは“１”と“０”とが反転しており、μ則では“１１１１１１１１”が正の最小の数値を示し、“１０００００００”が正の最大の数値を示すことに注意されたい。図中の「元の信号の大小関係を示す番号」の列が、非特許文献２（Ｇ．７１１）のμ則の具体例を示す表（Ｔａｂｌｅ ２ａ）の第８列に相当し、「元の信号の量子化値」の列が第７列に相当する。図１７（Ａ）は指数部（セグメント）が“１１１”の例を示しており、レベルが１増えるごとに、元の信号の大小関係を示す番号はｇ、元の信号の量子化値は２増えている。図１７（Ｂ）は指数部（セグメント）が“１１０” の例を示しており、レベルが１増えるごとに、元の信号の大小関係を示す番号はｇ、元の信号の量子化値は４増えている。図１７（Ｃ）は指数部（セグメント）が“００１” の例を示しており、レベルが１増えるごとに、元の信号の大小関係を示す番号はｇ、元の信号の量子化値は１２８増えている。図１７（Ｄ）は指数部（セグメント）が“０００” の例を示しており、レベルが１増えるごとに、元の信号の大小関係を示す番号はｇ、元の信号の量子化値は２５６増えている。なお、中間数値とは、処理Ｆ（）を行った後の値を指している。第２信号列Ｘと元の信号列と線形な信号列Ｓとの重みつき加算（ｇを重みとしてＸｇ＋Ｓ）によって、線形な関係に近づけることができる（重み付加算の結果、線形特性と圧伸特性の中間状態となる）。 [Concrete example]
In FIG. 17, as processing F () that approximates a linear relationship, the second signal sequence X, the original signal sequence, and the linear signal sequence S = {s (1), s (2),..., S (N)} An example of an 8-bit μ-law format (FIG. 2) in the case of performing weighted addition (X g + S with g as a weight) is shown. FIG. 17 shows only the case where the polarity is positive. In addition, in the exponent part (segment) and linear part (level) of the μ rule, “1” and “0” are reversed from the general sense, and “11111111” is the smallest positive value in the μ rule. Note that “10000000” indicates the maximum positive number. The column “number indicating the magnitude relationship of the original signal” in the figure corresponds to the eighth column of the table (Table 2a) showing a specific example of the μ rule of Non-Patent Document 2 (G.711). The column of “quantized values of the signal” corresponds to the seventh column. FIG. 17A shows an example in which the exponent part (segment) is “111”. As the level increases by 1, the number indicating the magnitude relationship of the original signal is g, and the quantized value of the original signal is 2 is increasing. FIG. 17B shows an example in which the exponent (segment) is “110”. Each time the level increases by 1, the number indicating the magnitude relationship of the original signal is g, and the quantized value of the original signal is 4 is increasing. FIG. 17C shows an example in which the exponent part (segment) is “001”. As the level increases by 1, the number indicating the magnitude relationship of the original signal is g, and the quantized value of the original signal is 128. is increasing. FIG. 17D shows an example in which the exponent part (segment) is “000”. As the level increases by 1, the number indicating the magnitude relationship of the original signal is g, and the quantized value of the original signal is 256. is increasing. The intermediate numerical value indicates a value after performing the processing F (). The weighted addition of the second signal sequence X, the original signal sequence, and the linear signal sequence S (X g + S with g as a weight) can approximate a linear relationship (the weighted addition results in linear characteristics and pressure Intermediate state of elongation characteristics).

算出用対応変換候補出力部１７０、４７０があらかじめ複数の算出用対応変換の候補を定めておく場合であれば、何種類かの重みｇを定めておけばよい。これらの重みｇを定める方法としては、学習データを用意しておき、学習データに適した重みｇを求める方法がある。これらの重みｇは、クラスタリングで設計することができる。図１８は、学習データを用いて、２つの重みｇ１、ｇ２を求める処理フロー例である。 If the calculation correspondence conversion candidate output units 170 and 470 determine a plurality of calculation correspondence conversion candidates in advance, several types of weights g may be determined. As a method for determining these weights g, there is a method of preparing learning data and obtaining a weight g suitable for the learning data. These weights g can be designed by clustering. FIG. 18 is an example of a processing flow for obtaining two weights g 1 and g 2 using learning data.

初期値として、重みｇ１、ｇ２を用意しておく。学習データの全フレームに対して、フレームごとに、それぞれの重みを用いた算出用対応変換Ｆ（）を使って符号化し、符号量を比較する（Ｓ１０１０）。重みｇ１の方が、符号量が少なかった全てのフレームに対して、最適な重みとなるように重みｇ１を計算し、新しい重みｇ１とする（Ｓ１０２０）。計算の方法としては、例えば、重みｇ１を微小に増減させて、全体の符号量が減る方向に動かし、収束させる方法がある。重みｇ２の方が、符号量が少なかった全てのフレームに対して、最適な重みとなるように重みｇ２を計算し、新しい重みｇ２とする（Ｓ１０３０）。あらかじめ定めた繰返し条件を満たすかを確認する（Ｓ１０４０）。なお、あらかじめ定めた条件とは、例えば繰返しの回数である。条件を満たさない場合はステップＳ１０１０に戻り、条件を満たす場合には処理を終了する。この処理で求められた重みｇ１、ｇ２によって特定される算出用対応変換Ｆ（）が、算出用対応変換候補出力部１７０、４７０があらかじめ定めておく算出用対応変換の候補である。 Weights g 1 and g 2 are prepared as initial values. All frames of the learning data are encoded for each frame using the calculation corresponding conversion F () using the respective weights, and the code amounts are compared (S1010). The weight g 1 is calculated so that the weight g 1 becomes an optimum weight for all frames having a smaller code amount, and is set as a new weight g 1 (S1020). As a calculation method, for example, there is a method in which the weight g 1 is slightly increased / decreased and moved in a direction in which the entire code amount is decreased to be converged. The weight g 2 is calculated so that the weight g 2 becomes an optimum weight for all frames having a smaller code amount, and is set as a new weight g 2 (S1030). It is checked whether a predetermined repetition condition is satisfied (S1040). The predetermined condition is, for example, the number of repetitions. If the condition is not satisfied, the process returns to step S1010. If the condition is satisfied, the process ends. The calculation correspondence conversion F () specified by the weights g 1 and g 2 obtained in this process is a calculation correspondence conversion candidate that the calculation correspondence conversion candidate output units 170 and 470 determine in advance.

図１９に、コンピュータの機能構成例を示す。本発明の符号化方法、復号化方法は、コンピュータ２０００の記録部２０２０に、本発明の各構成部としてコンピュータ２０００を動作させるプログラムを読み込ませ、制御部２０１０、入力部２０３０、出力部２０４０などを動作させることで、コンピュータに実行させることができる。また、コンピュータに読み込ませる方法としては、プログラムをコンピュータ読み取り可能な記録媒体に記録しておき、記録媒体からコンピュータに読み込ませる方法、サーバ等に記録されたプログラムを、電気通信回線等を通じてコンピュータに読み込ませる方法などがある。   FIG. 19 shows a functional configuration example of a computer. In the encoding method and decoding method of the present invention, the recording unit 2020 of the computer 2000 reads a program for operating the computer 2000 as each component of the present invention, and the control unit 2010, the input unit 2030, the output unit 2040, etc. By operating, it can be executed by a computer. In addition, as a method of causing the computer to read, the program is recorded on a computer-readable recording medium, and the program recorded on the server or the like is read into the computer through a telecommunication line or the like. There is a method to make it.

圧伸された信号列の振幅の例を示す図。The figure which shows the example of the amplitude of the signal train which was drawn. ８ビットのμ則の具体的な形式を示す図。The figure which shows the specific format of 8-bit micro rule. 符号化装置の機能構成例を示す図。The figure which shows the function structural example of an encoding apparatus. 符号化装置の処理フロー例を示す図。The figure which shows the process flow example of an encoding apparatus. 復号化装置の機能構成例を示す図。The figure which shows the function structural example of a decoding apparatus. 復号化装置の処理フロー例を示す図。The figure which shows the example of a processing flow of a decoding apparatus. 第１実施形態の符号化装置の機能構成例を示す図。The figure which shows the function structural example of the encoding apparatus of 1st Embodiment. 第１実施形態の符号化装置の処理フロー例を示す図。The figure which shows the example of a processing flow of the encoding apparatus of 1st Embodiment. 第１実施形態の復号化装置の機能構成例を示す図。The figure which shows the function structural example of the decoding apparatus of 1st Embodiment. 第１実施形態の復号化装置の処理フロー例を示す図。The figure which shows the example of a processing flow of the decoding apparatus of 1st Embodiment. 第１実施形態変形例の符号化装置の機能構成例を示す図。The figure which shows the function structural example of the encoding apparatus of 1st Embodiment modification. 第１実施形態変形例の符号化装置の処理フロー例を示す図。The figure which shows the example of a processing flow of the encoding apparatus of 1st Embodiment modification. 第２実施形態の符号化装置の機能構成例を示す図。The figure which shows the function structural example of the encoding apparatus of 2nd Embodiment. 第２実施形態の符号化装置の処理フロー例を示す図。The figure which shows the example of a processing flow of the encoding apparatus of 2nd Embodiment. 第２実施形態変形例の符号化装置の機能構成例を示す図。The figure which shows the function structural example of the encoding apparatus of 2nd Embodiment modification. 第２実施形態変形例の符号化装置の処理フロー例を示す図。The figure which shows the example of a processing flow of the encoding apparatus of 2nd Embodiment modification. 線形な関係に近づける処理Ｆ（）として第２信号列のサンプル値の振幅ｘと元の信号列のサンプル値の振幅ｓとの重みつき加算を行った場合の指数部が“１１１”と“１１０”の例を示す図。As processing F () that approximates a linear relationship, the exponent parts when the weighted addition of the amplitude x of the sample value of the second signal sequence and the amplitude s of the sample value of the original signal sequence are “111” and “110” FIG. 線形な関係に近づける処理Ｆ（）として第２信号列のサンプル値の振幅ｘと元の信号列のサンプル値の振幅ｓとの重みつき加算を行った場合の指数部が“００１”と“０００”の例を示す図。As a process F () that approximates a linear relationship, the exponent part is “001” and “000” when weighted addition of the amplitude x of the sample value of the second signal sequence and the amplitude s of the sample value of the original signal sequence is performed. FIG. 学習データを用いて、２つの重みを求める処理フロー例を示す図。The figure which shows the example of a processing flow which calculates | requires two weights using learning data. コンピュータの機能構成例を示す図。The figure which shows the function structural example of a computer.

符号の説明Explanation of symbols

１００、２００、４００、５００、８００ 符号化装置
１３０、８３０ 予測値算出部 １３１ 算出用線形対応手段
１３２ 算出手段 １３３ 第２予測手段
１７０、４７０ 算出用対応変換候補出力部 １８０ 最適選定部
２１０、８１０線形予測部 ２１１ 分析用線形対応手段
２１２ 分析係数手段 ３００、９００ 復号化装置
３３０、９３０ 予測値算出部 ３３１ 復号線形対応手段
３３２ 復号予測手段 ３３３ 第２復号手段
４８０ 最適選定部 ８２０ 量子化部
８４０ 減算部 ８５０ 係数符号化部
８６０ 残差符号化部 ８７０ フレーム分割部
９１０ 残差復号化部 ９２０ 係数復号化部
９４０ 加算部 100, 200, 400, 500, 800 Encoding device 130, 830 Predicted value calculation unit 131 Calculation linear correspondence unit 132 Calculation unit 133 Second prediction unit 170, 470 Calculation corresponding conversion candidate output unit 180 Optimal selection unit 210, 810 Linear prediction unit 211 Analysis linear correspondence unit 212 Analysis coefficient unit 300, 900 Decoding device 330, 930 Predicted value calculation unit 331 Decoding linear correspondence unit 332 Decoding prediction unit 333 Second decoding unit 480 Optimal selection unit 820 Quantization unit 840 Subtraction Unit 850 coefficient encoding unit 860 residual encoding unit 870 frame dividing unit 910 residual decoding unit 920 coefficient decoding unit 940 addition unit

Claims (20)

線形PCM信号により構成される元の信号列の大小関係を示す番号系列（以下、「第２信号列」という）を符号化する符号化方法であって、
前記第２信号列を用いて、線形予測係数を求める線形予測ステップと、
前記線形予測係数を量子化して量子化線形予測係数を求める量子化ステップと、
前記第２信号列と前記量子化線形予測係数を用いて、第２予測値列を求める予測値算出ステップと、
前記第２信号列と前記第２予測値列との差を求め、予測残差列を求める減算ステップと、
前記量子化線形予測係数を符号化し、予測係数符号を求める係数符号化ステップと、
前記予測残差列を符号化し、予測残差符号を求める残差符号化ステップと
を有し、
前記予測値算出ステップは、
前記第２信号列に含まれる各信号と前記元の信号列に含まれる各信号との中間的な信号による信号列を生成する処理である算出用対応変換処理によって、算出用信号列に変換する算出用対応変換サブステップと、
前記算出用信号列と前記量子化線形予測係数を用いて予測値列を求める算出サブステップと、
前記予測値列の各信号に対して、前記算出用対応変換処理の逆の処理をして得られる第２予測値により構成される第２予測値列を求める第２予測サブステップと、
を有し、
複数種類の前記算出用対応変換処理の中から符号量または符号量の推定値が最小になる算出用対応変換処理を求め、当該算出用対応変換処理を特定する情報と、当該算出用対応変換処理に対応する予測残差列とを出力する最適選択ステップを更に有し、
前記残差符号化ステップは、前記最適選択ステップで得られた予測残差列を符号化する
ことを特徴とする符号化方法。 An encoding method for encoding a number sequence (hereinafter referred to as “second signal sequence”) indicating a magnitude relationship of an original signal sequence composed of linear PCM signals ,
A linear prediction step for obtaining a linear prediction coefficient using the second signal sequence;
A quantization step of quantizing the linear prediction coefficient to obtain a quantized linear prediction coefficient;
Using the quantized linear prediction coefficients and the second signal sequence, and the predicted value calculation step of obtaining a second predicted value sequence,
A subtraction step of obtaining a difference between the second signal sequence and the second predicted value sequence and obtaining a prediction residual sequence;
Encoding the quantized linear prediction coefficients, and coefficient coding step asking you to prediction coefficient code,
The prediction residual sequence encoding, and a residual encoding step asking you to prediction residual code,
The predicted value calculation step includes:
The signal is converted into a calculation signal string by a calculation corresponding conversion process that is a process for generating a signal string based on an intermediate signal between each signal included in the second signal string and each signal included in the original signal string. A corresponding conversion sub-step for calculation;
A calculation sub-step for obtaining a predicted value sequence using the calculation signal sequence and the quantized linear prediction coefficient;
A second prediction sub-step for obtaining a second predicted value sequence composed of a second predicted value obtained by performing the reverse process of the calculation corresponding conversion process for each signal of the predicted value sequence;
Have
Obtains a plurality of types code quantity from the calculation for the corresponding conversion processing or the code amount of the estimated value is calculated for the corresponding conversion process to minimize, information specifying for the calculation corresponding conversion process, the corresponding conversion processing the calculation And an optimal selection step for outputting a prediction residual sequence corresponding to
In the encoding method, the residual encoding step encodes the prediction residual sequence obtained in the optimal selection step . 線形PCM信号により構成される元の信号列の大小関係を示す番号系列（以下、「第２信号列」という）を符号化する符号化方法であって、
前記第２信号列を用いて、線形予測係数を求める線形予測ステップと、
前記線形予測係数を量子化して量子化線形予測係数を求める量子化ステップと、
前記第２信号列に含まれる各信号と前記元の信号列に含まれる各信号との中間的な信号による信号列を生成する処理である算出用対応変換の候補を、あらかじめ定めた複数の算出用対応変換の候補の中からあらかじめ定めた手順で１つずつ出力する算出用対応変換候補出力ステップと、
前記算出用対応変換の候補ごとに、前記第２信号列と前記量子化線形予測係数を用いて、第２予測値列を求める予測値算出ステップと、
前記算出用対応変換の候補ごとに、前記第２信号列と前記第２予測値列との差を求め、予測残差列を求める減算ステップと、
あらかじめ定めた条件を満たすまで実行された繰返しの間に前記算出用対応変換候補出力ステップが出力した複数の算出用対応変換の候補の中から、前記予測残差列から求めた符号量の推定値を最小にする算出用対応変換を選び、選ばれた算出用対応変換を特定する処理情報と当該算出用対応変換を用いた時の予測残差列を出力する最適選定ステップと、
前記量子化線形予測係数を符号化し、予測係数符号を出力する係数符号化ステップと、
前記予測残差列を符号化し、予測残差符号を出力する残差符号化ステップと、
を有し、
前記予測値算出ステップは、
前記第２信号列を、算出用対応変換の候補を用いて算出用信号列に変換する算出用線形対応サブステップと、
前記算出用信号列と前記量子化線形予測係数を用いて予測値列を求める算出サブステップと、
前記予測値列の各信号に対して、前記算出用対応変換の候補の逆の処理をして得られる第２予測値により構成される第２予測値列を求める第２予測サブステップと、
を有する符号化方法。 An encoding method for encoding a number sequence (hereinafter referred to as “second signal sequence”) indicating a magnitude relationship of an original signal sequence composed of linear PCM signals ,
A linear prediction step for obtaining a linear prediction coefficient using the second signal sequence;
A quantization step of quantizing the linear prediction coefficient to obtain a quantized linear prediction coefficient;
A plurality of predetermined calculation candidates for calculation corresponding conversion for calculation, which is a process for generating a signal sequence based on an intermediate signal between each signal included in the second signal sequence and each signal included in the original signal sequence A corresponding conversion candidate output step for calculation, which outputs one by one according to a predetermined procedure from among candidate conversions for
For each candidate of the calculation corresponding conversion, by using the quantized linear prediction coefficients and the second signal sequence, and the predicted value calculation step of obtaining a second predicted value sequence,
A subtraction step for obtaining a difference between the second signal sequence and the second predicted value sequence for each candidate for conversion for calculation, and obtaining a prediction residual sequence;
An estimated value of the code amount obtained from the prediction residual sequence from among a plurality of calculation corresponding conversion candidates output by the calculation corresponding conversion candidate output step during iterations executed until a predetermined condition is satisfied. An optimal selection step of selecting a corresponding conversion for calculation that minimizes the processing information for specifying the selected conversion correspondence for calculation and a prediction residual sequence when using the corresponding conversion for calculation;
A coefficient encoding step of encoding the quantized linear prediction coefficient and outputting a prediction coefficient code;
A residual encoding step of encoding the prediction residual sequence and outputting a prediction residual code;
Have
The predicted value calculation step includes:
A linear correspondence sub-step for calculation for converting the second signal sequence into a signal sequence for calculation using a candidate for conversion for calculation;
A calculation sub-step for obtaining a predicted value sequence using the calculation signal sequence and the quantized linear prediction coefficient;
A second prediction sub-step for obtaining a second predicted value sequence composed of a second predicted value obtained by performing a reverse process of the calculation corresponding conversion candidate for each signal of the predicted value sequence;
An encoding method comprising: 線形PCM信号により構成される元の信号列の大小関係を示す番号系列（以下、「第２信号列」という）を符号化する符号化方法であって、
前記第２信号列を用いて、線形予測係数を求める線形予測ステップと、
前記線形予測係数を量子化して量子化線形予測係数を求める量子化ステップと、
前記量子化線形予測係数を符号化し、予測係数符号を出力する係数符号化ステップと、
前記第２信号列に含まれる各信号と前記元の信号列に含まれる各信号との中間的な信号による信号列を生成する処理である算出用対応変換の候補を、あらかじめ定めた複数の算出用対応変換の候補の中からあらかじめ定めた手順で１つずつ出力する算出用対応変換候補出力ステップと、
前記算出用対応変換の候補ごとに、前記第２信号列と前記量子化線形予測係数を用いて、第２予測値列を求める予測値算出ステップと、
前記算出用対応変換の候補ごとに、前記第２信号列と前記第２予測値列との差を求め、予測残差列を求める減算ステップと、
前記算出用対応変換の候補ごとに、前記予測残差列を符号化し、予測残差符号を出力する残差符号化ステップと、
あらかじめ定めた条件を満たすまで実行された繰返しの間に前記算出用対応変換候補出力ステップが出力した複数の算出用対応変換の候補の中から、前記予測係数符号と前記予測残差符号を合わせた符号量を最小にする算出用対応変換を選び、選ばれた算出用対応変換を特定する処理情報と当該算出用対応変換を用いた時の予測残差符号を出力する最適選定ステップと
を有し、
前記予測値算出ステップは、
前記第２信号列を、前記処理情報によって特定される算出用対応変換の候補を用いて算出用信号列に変換する算出用線形対応サブステップと、
前記算出用信号列と前記量子化線形予測係数を用いて予測値列を求める算出サブステップと、
前記予測値列の各信号に対して、前記算出用対応変換の候補の逆の処理をして得られる第２予測値により構成される第２予測値列を求める第２予測サブステップと、
を有する符号化方法。 An encoding method for encoding a number sequence (hereinafter referred to as “second signal sequence”) indicating a magnitude relationship of an original signal sequence composed of linear PCM signals ,
A linear prediction step for obtaining a linear prediction coefficient using the second signal sequence;
A quantization step of quantizing the linear prediction coefficient to obtain a quantized linear prediction coefficient;
A coefficient encoding step of encoding the quantized linear prediction coefficient and outputting a prediction coefficient code;
A plurality of predetermined calculation candidates for calculation corresponding conversion for calculation, which is a process for generating a signal sequence based on an intermediate signal between each signal included in the second signal sequence and each signal included in the original signal sequence A corresponding conversion candidate output step for calculation, which outputs one by one according to a predetermined procedure from among candidate conversions for
For each candidate of the calculation corresponding conversion, by using the quantized linear prediction coefficients and the second signal sequence, and the predicted value calculation step of obtaining a second predicted value sequence,
A subtraction step for obtaining a difference between the second signal sequence and the second predicted value sequence for each candidate for conversion for calculation, and obtaining a prediction residual sequence;
A residual encoding step for encoding the prediction residual sequence and outputting a prediction residual code for each candidate for the corresponding transform for calculation;
The prediction coefficient code and the prediction residual code are combined from among a plurality of calculation corresponding conversion candidates output by the calculation corresponding conversion candidate output step during the repetition executed until a predetermined condition is satisfied. An optimum selection step for selecting a corresponding conversion for calculation that minimizes the amount of code and specifying the selected corresponding conversion for calculation and outputting a prediction residual code when using the corresponding conversion for calculation. ,
The predicted value calculation step includes:
A linear correspondence sub-step for calculation that converts the second signal sequence into a signal sequence for calculation using a candidate for conversion correspondence for calculation specified by the processing information;
A calculation sub-step for obtaining a predicted value sequence using the calculation signal sequence and the quantized linear prediction coefficient;
A second prediction sub-step for obtaining a second predicted value sequence composed of a second predicted value obtained by performing a reverse process of the calculation corresponding conversion candidate for each signal of the predicted value sequence;
An encoding method comprising: 請求項１から３のいずれかに記載の符号化方法であって、  The encoding method according to any one of claims 1 to 3,
前記中間的な信号による信号列は、前記第２信号列に含まれる各信号と前記元の信号列に含まれる各信号との重み付け加算により得られる信号による信号列である  The signal sequence based on the intermediate signal is a signal sequence based on signals obtained by weighted addition of each signal included in the second signal sequence and each signal included in the original signal sequence.
符号化方法。  Encoding method. 請求項１から４のいずれかに記載の符号化方法であって、
前記線形予測ステップは、
前記第２信号列に含まれる各信号を、前記元の信号列に含まれる各信号と線形な関係の分析用信号に変換して得られる分析用信号列を得る分析用線形対応サブステップと、
前記分析用信号列を線形予測分析して線形予測係数を求める分析係数サブステップと
を有することを特徴とする符号化方法。 An encoding method according to any one of claims 1 to 4 , comprising:
The linear prediction step includes:
Each signal included in the second signal sequence, the signal and the linear analytical linear corresponding sub-step Ru obtain an analytical signal sequence obtained by converting the signal for analysis of relationships included in the original signal sequence When,
An analysis coefficient substep for obtaining a linear prediction coefficient by performing linear prediction analysis on the signal sequence for analysis. 請求項１から４のいずれかに記載の符号化方法であって、
前記線形予測ステップは、
前記第２信号列に含まれる各信号と前記元の信号列に含まれる各信号との中間的な信号である分析用信号により構成される分析用信号列を得る分析用線形対応サブステップと、
前記分析用信号列を線形予測分析して線形予測係数を求める分析係数サブステップと
を有することを特徴とする符号化方法。 An encoding method according to any one of claims 1 to 4, comprising:
The linear prediction step includes:
An analysis linear correspondence sub-step for obtaining an analysis signal sequence constituted by an analysis signal that is an intermediate signal between each signal included in the second signal sequence and each signal included in the original signal sequence;
An analysis coefficient substep for obtaining a linear prediction coefficient by performing linear prediction analysis on the signal sequence for analysis. 線形PCM信号により構成される元の信号列の大小関係を示す番号系列（以下、「第２信号列」という）に復号化する復号化方法であって、
予測残差符号を用いて、予測残差列を求める残差復号化ステップと、
予測係数符号から量子化線形予測係数を求める係数復号化ステップと、
前記第２信号列に含まれる各信号を前記元の信号列に含まれる各信号との中間的な信号による信号列を生成する処理である算出用対応変換処理を特定するための処理情報と、復号化された過去の第２信号列と、前記量子化線形予測係数を用いて、第２予測値列を求める予測値算出ステップと、
前記第２予測値列と前記予測残差列とを加算して前記第２信号列を求める加算ステップと
を有し、
前記予測値算出ステップは、
前記過去の第２信号列を、前記処理情報によって特定された算出用対応変換処理によって、算出用信号列に変換する復号線形対応サブステップと、
前記算出用信号列と前記量子化線形予測係数を用いて予測値列を求める復号予測サブステップと、
前記予測値列の各信号に対して、前記算出用対応変換処理の逆の処理をして得られる第２予測値により構成される第２予測値列を求める第２復号サブステップと
を有する復号化方法。 A decoding method for decoding into a number sequence (hereinafter referred to as “second signal sequence”) indicating the magnitude relationship of an original signal sequence composed of linear PCM signals ,
A residual decoding step for obtaining a prediction residual sequence using the prediction residual code;
A coefficient decoding step for obtaining a quantized linear prediction coefficient from the prediction coefficient code;
Processing information for specifying a corresponding conversion process for calculation, which is a process of generating a signal sequence based on an intermediate signal between each signal included in the second signal sequence and each signal included in the original signal sequence; a second signal sequence of the past decoded, by using the quantized linear prediction coefficients, the predicted value calculation step of obtaining a second predicted value sequence,
Adding the second predicted value sequence and the predicted residual sequence to obtain the second signal sequence;
The predicted value calculation step includes:
A decoding linear correspondence sub-step of converting the past second signal sequence into a calculation signal sequence by a calculation correspondence conversion process specified by the processing information;
A decoding prediction substep for obtaining a prediction value sequence using the signal sequence for calculation and the quantized linear prediction coefficient;
A second decoding sub-step for obtaining a second predicted value sequence composed of a second predicted value obtained by performing a reverse process of the corresponding conversion conversion process for each signal of the predicted value sequence Method. 請求項７に記載の復号化方法であって、  The decoding method according to claim 7, comprising:
前記中間的な信号による信号列は、前記第２信号列に含まれる各信号と前記元の信号列に含まれる各信号との重み付け加算により得られる信号による信号列である  The signal sequence based on the intermediate signal is a signal sequence based on signals obtained by weighted addition of each signal included in the second signal sequence and each signal included in the original signal sequence.
復号化方法。  Decryption method. 線形PCM信号により構成される元の信号列の大小関係を示す番号系列（以下、「第２信号列」という）を符号化する符号化装置であって、
前記第２信号列を用いて、線形予測係数を求める線形予測部と、
前記線形予測係数を量子化して量子化線形予測係数を求める量子化部と、
前記第２信号列と前記量子化線形予測係数を用いて、第２予測値列を求める予測値算出部と、
前記第２信号列と前記第２予測値列との差を求め、予測残差列を求める減算部と、
前記量子化線形予測係数を符号化し、予測係数符号を求める係数符号化部と、
前記予測残差列を符号化し、予測残差符号を求める残差符号化部と
を備え、
前記予測値算出部は、
前記第２信号列に含まれる各信号と前記元の信号列に含まれる各信号との中間的な信号による信号列を生成する処理である算出用対応変換処理によって、算出用信号列に変換する算出用対応変換部と、
前記算出用信号列と前記量子化線形予測係数を用いて予測値列を求める算出部と、
前記予測値列の各信号に対して、前記算出用対応変換処理の逆の処理をして得られる第２予測値により構成される第２予測値列を求める第２予測部と、
を有し、
複数種類の前記算出用対応変換処理の中から符号量または符号量の推定値が最小になる算出用対応変換処理を求め、当該算出用対応変換処理を特定する情報と、当該算出用対応変換処理に対応する予測残差列とを出力する最適選択部を更に有し、
前記残差符号化部は、前記最適選択ステップで得られた予測残差列を符号化する
ことを特徴とする符号化装置。 An encoding device that encodes a number sequence (hereinafter referred to as “second signal sequence”) indicating a magnitude relationship of an original signal sequence composed of linear PCM signals ,
A linear prediction unit for obtaining a linear prediction coefficient using the second signal sequence;
A quantization unit that quantizes the linear prediction coefficient to obtain a quantized linear prediction coefficient;
Using the quantized linear prediction coefficients and the second signal sequence, and the predicted value calculation unit for obtaining a second prediction value column,
A subtraction unit for obtaining a difference between the second signal sequence and the second predicted value sequence and obtaining a prediction residual sequence;
Encoding the quantized linear prediction coefficients, and coefficient coding unit asking you to prediction coefficient code,
The prediction residual sequence encoding, and a residual coding unit asking you to prediction residual code,
The predicted value calculation unit
The signal is converted into a calculation signal string by a calculation corresponding conversion process that is a process for generating a signal string based on an intermediate signal between each signal included in the second signal string and each signal included in the original signal string. A corresponding conversion unit for calculation;
A calculation unit for obtaining a predicted value sequence using the calculation signal sequence and the quantized linear prediction coefficient;
A second prediction unit for obtaining a second predicted value sequence composed of a second predicted value obtained by performing a reverse process of the calculation correspondence conversion process for each signal of the predicted value sequence;
Have
Obtains a plurality of types code quantity from the calculation for the corresponding conversion processing or the code amount of the estimated value is calculated for the corresponding conversion process to minimize, information specifying for the calculation corresponding conversion process, the corresponding conversion processing the calculation And an optimal selection unit that outputs a prediction residual sequence corresponding to
The encoding apparatus characterized in that the residual encoding unit encodes the prediction residual sequence obtained in the optimal selection step . 線形PCM信号により構成される元の信号列の大小関係を示す番号系列（以下、「第２信号列」という）を符号化する符号化装置であって、
前記第２信号列を用いて、線形予測係数を求める線形予測部と、
前記線形予測係数を量子化して量子化線形予測係数を求める量子化部と、
前記第２信号列に含まれる各信号と前記元の信号列に含まれる各信号との中間的な信号による信号列を生成する処理である算出用対応変換の候補を、あらかじめ定めた複数の算出用対応変換の候補の中からあらかじめ定めた手順で１つずつ出力する算出用対応変換候補出力部と、
前記算出用対応変換の候補ごとに、前記第２信号列と前記量子化線形予測係数を用いて、第２予測値列を求める予測値算出部と、
前記算出用対応変換の候補ごとに、前記第２信号列と前記第２予測値列との差を求め、予測残差列を求める減算部と、
あらかじめ定めた条件を満たすまで実行された繰返しの間に前記算出用対応変換候補出力部が出力した複数の算出用対応変換の候補の中から、前記予測残差列から求めた符号量の推定値を最小にする算出用対応変換を選び、選ばれた算出用対応変換を特定する処理情報と当該算出用対応変換を用いた時の予測残差列を出力する最適選定部と、
前記量子化線形予測係数を符号化し、予測係数符号を出力する係数符号化部と、
前記予測残差列を符号化し、予測残差符号を出力する残差符号化部と、
を備え、
前記予測値算出部は、
前記第２信号列を、算出用対応変換の候補を用いて算出用信号列に変換する算出用線形対応手段と、
前記算出用信号列と前記量子化線形予測係数を用いて予測値列を求める算出手段と、
前記予測値列の各信号に対して、前記算出用対応変換の候補の逆の処理をして得られる第２予測値により構成される第２予測値列を求める第２予測手段と、
を有する符号化装置。 An encoding device that encodes a number sequence (hereinafter referred to as “second signal sequence”) indicating a magnitude relationship of an original signal sequence composed of linear PCM signals ,
A linear prediction unit for obtaining a linear prediction coefficient using the second signal sequence;
A quantization unit that quantizes the linear prediction coefficient to obtain a quantized linear prediction coefficient;
A plurality of predetermined calculation candidates for calculation corresponding conversion for calculation, which is a process for generating a signal sequence based on an intermediate signal between each signal included in the second signal sequence and each signal included in the original signal sequence A corresponding conversion candidate output unit for calculation that outputs one by one according to a predetermined procedure from among candidate conversions for
For each candidate of the calculation corresponding conversion, by using the quantized linear prediction coefficients and the second signal sequence, and the predicted value calculation unit for obtaining a second prediction value column,
A subtraction unit that obtains a difference between the second signal sequence and the second predicted value sequence and obtains a prediction residual sequence for each candidate for conversion for calculation;
An estimated value of the code amount obtained from the prediction residual sequence from among a plurality of calculation correspondence conversion candidates output by the calculation correspondence conversion candidate output unit during iterations executed until a predetermined condition is satisfied. An optimal selection unit that selects a corresponding conversion for calculation that minimizes and outputs processing information that identifies the selected corresponding conversion for calculation and a prediction residual sequence when using the corresponding conversion for calculation;
A coefficient encoding unit that encodes the quantized linear prediction coefficient and outputs a prediction coefficient code;
A residual encoding unit that encodes the prediction residual sequence and outputs a prediction residual code;
With
The predicted value calculation unit
A linear correspondence unit for calculation for converting the second signal sequence into a signal sequence for calculation using a candidate for conversion for calculation;
Calculating means for obtaining a predicted value sequence using the calculation signal sequence and the quantized linear prediction coefficient;
Second prediction means for obtaining a second predicted value sequence composed of a second predicted value obtained by performing the reverse processing of the candidate for conversion for calculation for each signal of the predicted value sequence;
An encoding device. 線形PCM信号により構成される元の信号列の大小関係を示す番号系列（以下、「第２信号列」という）を符号化する符号化装置であって、
前記第２信号列を用いて、線形予測係数を求める線形予測部と、
前記線形予測係数を量子化して量子化線形予測係数を求める量子化部と、
前記量子化線形予測係数を符号化し、予測係数符号を出力する係数符号化部と、
前記第２信号列に含まれる各信号と前記元の信号列に含まれる各信号との中間的な信号による信号列を生成する処理である算出用対応変換の候補を、あらかじめ定めた複数の算出用対応変換の候補の中からあらかじめ定めた手順で１つずつ出力する算出用対応変換候補出力部と、
前記算出用対応変換の候補ごとに、前記第２信号列と前記量子化線形予測係数を用いて、第２予測値列を求める予測値算出部と、
前記算出用対応変換の候補ごとに、前記第２信号列と前記第２予測値列との差を求め、予測残差列を求める減算部と、
前記算出用対応変換の候補ごとに、前記予測残差列を符号化し、予測残差符号を出力する残差符号化部と、
あらかじめ定めた条件を満たすまで実行された繰返しの間に前記算出用対応変換候補出力部が出力した複数の算出用対応変換の候補の中から、前記予測係数符号と前記予測残差符号を合わせた符号量を最小にする算出用対応変換を選び、選ばれた算出用対応変換を特定する処理情報と当該算出用対応変換を用いた時の予測残差符号を出力する最適選定部と
を備え、
前記予測値算出部は、
前記第２信号列を、算出用対応変換の候補を用いて算出用信号列に変換する算出用線形対応手段と、
前記算出用信号列と前記量子化線形予測係数を用いて予測値列を求める算出手段と、
前記予測値列の各信号に対して、前記算出用対応変換の候補の逆の処理をして得られる第２予測値により構成される第２予測値列を求める第２予測手段と、
を有する符号化装置。 An encoding device that encodes a number sequence (hereinafter referred to as “second signal sequence”) indicating a magnitude relationship of an original signal sequence composed of linear PCM signals ,
A linear prediction unit for obtaining a linear prediction coefficient using the second signal sequence;
A quantization unit that quantizes the linear prediction coefficient to obtain a quantized linear prediction coefficient;
A coefficient encoding unit that encodes the quantized linear prediction coefficient and outputs a prediction coefficient code;
A plurality of predetermined calculation candidates for calculation corresponding conversion for calculation, which is a process for generating a signal sequence based on an intermediate signal between each signal included in the second signal sequence and each signal included in the original signal sequence A corresponding conversion candidate output unit for calculation that outputs one by one according to a predetermined procedure from among candidate conversions for
For each candidate of the calculation corresponding conversion, by using the quantized linear prediction coefficients and the second signal sequence, and the predicted value calculation unit for obtaining a second prediction value column,
A subtraction unit that obtains a difference between the second signal sequence and the second predicted value sequence and obtains a prediction residual sequence for each candidate for conversion for calculation;
A residual encoding unit that encodes the prediction residual sequence and outputs a prediction residual code for each candidate for the corresponding transform for calculation;
The prediction coefficient code and the prediction residual code are combined from among a plurality of calculation correspondence conversion candidates output by the calculation correspondence conversion candidate output unit during iterations executed until a predetermined condition is satisfied. A calculation corresponding conversion for minimizing the code amount, processing information for specifying the selected calculation corresponding conversion, and an optimum selection unit that outputs a prediction residual code when using the calculation corresponding conversion, and
The predicted value calculation unit
A linear correspondence unit for calculation for converting the second signal sequence into a signal sequence for calculation using a candidate for conversion for calculation;
Calculating means for obtaining a predicted value sequence using the calculation signal sequence and the quantized linear prediction coefficient;
Second prediction means for obtaining a second predicted value sequence composed of a second predicted value obtained by performing the reverse processing of the candidate for conversion for calculation for each signal of the predicted value sequence;
An encoding device. 請求項９から１１のいずれかに記載の符号化装置であって、  The encoding device according to any one of claims 9 to 11,
前記中間的な信号による信号列は、前記第２信号列に含まれる各信号と前記元の信号列に含まれる各信号との重み付け加算により得られる信号による信号列である  The signal sequence based on the intermediate signal is a signal sequence based on signals obtained by weighted addition of each signal included in the second signal sequence and each signal included in the original signal sequence.
符号化装置。  Encoding device. 請求項９から１２のいずれかに記載の符号化装置であって、
前記線形予測部は、
前記第２信号列に含まれる各信号を、前記元の信号列に含まれる各信号と線形な関係の分析用信号に変換して得られる分析用信号列を得る分析用線形対応手段と、
前記分析用信号列を線形予測分析して線形予測係数を求める分析係数部と
を有することを特徴とする符号化装置。 A coding apparatus according to claim 9 1 2,
The linear prediction unit
Each signal included in the second signal sequence, and the signal and the resulting Ru analytical linear relation means the analysis signal sequence obtained by converting the signal for analysis of linear relationships included in the original signal sequence ,
And an analysis coefficient unit for obtaining a linear prediction coefficient by performing linear prediction analysis on the signal sequence for analysis. 請求項９から１２のいずれかに記載の符号化装置であって、
前記線形予測部は、
前記第２信号列に含まれる各信号と、前記元の信号列に含まれる各信号との中間的な信号である分析用信号により構成される分析用信号列を得る分析用線形対応手段と、
前記分析用信号列を線形予測分析して線形予測係数を求める分析係数手段と
を有することを特徴とする符号化装置。 A coding apparatus according to claim 9 1 2,
The linear prediction unit
An analysis linear correspondence means for obtaining an analysis signal sequence composed of an analysis signal that is an intermediate signal between each signal included in the second signal sequence and each signal included in the original signal sequence;
And an analysis coefficient means for obtaining a linear prediction coefficient by performing a linear prediction analysis on the signal sequence for analysis. 線形PCM信号により構成される元の信号列の大小関係を示す番号系列（以下、「第２信号列」という）に復号化する復号化装置であって、
予測残差符号を用いて、予測残差列を求める残差復号化部と、
予測係数符号から量子化線形予測係数を求める係数復号化部と、
前記第２信号列に含まれる各信号を前記元の信号列に含まれる各信号との中間的な信号による信号列を生成する処理である算出用対応変換処理を特定するための処理情報と、復号化された過去の第２信号列と、前記量子化線形予測係数を用いて、第２予測値列を求める予測値算出部と、
前記第２予測値列と前記予測残差列とを加算して前記第２信号列を求める加算部と
を備え、
前記予測値算出部は、
前記過去の第２信号列を、前記処理情報によって特定された算出用対応変換処理によって、算出用信号列に変換する復号線形対応手段と、
前記算出用信号列と前記量子化線形予測係数を用いて予測値列を求める復号予測手段と、
前記予測値列の各信号に対して、前記算出用対応変換処理の逆の処理をして得られる第２予測値により構成される第２予測値列を求める第２復号手段と
を有する復号化装置。 A decoding device for decoding into a number sequence (hereinafter referred to as “second signal sequence”) indicating a magnitude relationship of an original signal sequence composed of linear PCM signals ,
A residual decoding unit for obtaining a prediction residual sequence using the prediction residual code;
A coefficient decoding unit for obtaining a quantized linear prediction coefficient from the prediction coefficient code;
Processing information for specifying a corresponding conversion process for calculation, which is a process of generating a signal sequence based on an intermediate signal between each signal included in the second signal sequence and each signal included in the original signal sequence; a second signal sequence of the past decoded, by using the quantized linear prediction coefficients, the predicted value calculation unit for obtaining a second prediction value column,
An adder that adds the second predicted value sequence and the predicted residual sequence to obtain the second signal sequence;
The predicted value calculation unit
Decoding linear correspondence means for converting the past second signal sequence into a calculation signal sequence by a calculation correspondence conversion process specified by the processing information;
Decoding prediction means for obtaining a predicted value sequence using the signal sequence for calculation and the quantized linear prediction coefficient;
Decoding comprising: a second decoding unit that obtains a second predicted value sequence composed of a second predicted value obtained by performing a reverse process of the corresponding conversion conversion process for each signal of the predicted value sequence apparatus. 請求項１５に記載の復号化装置であって、The decoding device according to claim 15, comprising:
前記中間的な信号による信号列は、前記第２信号列に含まれる各信号と前記元の信号列に含まれる各信号との重み付け加算により得られる信号による信号列である  The signal sequence based on the intermediate signal is a signal sequence based on signals obtained by weighted addition of each signal included in the second signal sequence and each signal included in the original signal sequence.
復号化装置。  Decryption device. 請求項１から６のいずれかに記載の符号化方法の各ステップをコンピュータに実行させる符号化プログラム。 The encoding program which makes a computer perform each step of the encoding method in any one of Claim 1 to 6 . 請求項７または８記載の復号化方法の各ステップをコンピュータに実行させる復号化プログラム。 A decoding program for causing a computer to execute each step of the decoding method according to claim 7 or 8. 請求項１７記載の符号化プログラムを記録したコンピュータ読み取り可能な記録媒体。   A computer-readable recording medium on which the encoding program according to claim 17 is recorded. 請求項１８記載の復号化プログラムを記録したコンピュータ読み取り可能な記録媒体。   A computer-readable recording medium on which the decoding program according to claim 18 is recorded.
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