Encoder, decoder, and method therefor

Provided is an encoder which can effectively encode/decode spectrum data of a broad frequency signal in a high frequency range, can dramatically reduce the number of the arithmetic operations to be performed, and can improve the quality of the decoded signal. The encoder comprises a first layer coding unit (202) which encodes an input signal in a low frequency range below a predetermined frequency to generate first coded information, a first layer decoding unit (203) which decodes the first coded information to generate a decoded signal, and a second layer coding unit (206) which splits the input signal in a high frequency range above a predetermined frequency, into a plurality of sub-bands, presumes the respective sub-hands from the input signal or decoded signal, partially selects a spectrum component within each sub-band, and calculates an amplitude adjustment parameter used to adjust the amplitude of the selected spectrum component to thereby generate second coding information.

TECHNICAL FIELD

The present invention relates to an encoding apparatus, a decoding apparatus, and a method therefor that are used for a communication system which transmits a signal by encoding the signal.

BACKGROUND ART

When speech or sound signals are transmitted by a packet communication system, a mobile communication system, or the like as represented by Internet communications, compressing and encoding techniques are often used to increase transmission efficiency of the speech or sound signals. Further, in recent years, while encoding speech or sound signals at simply a low bit rate, there is an increasing demand for a technique of encoding speech or sound signals of a broader band.

To meet this need, various techniques have been developed to encode broadband speech or sound signals without substantially increasing the amount of information after encoding. For example, according to a technique disclosed in Patent Literature 1, an encoding apparatus calculates a parameter to generate a spectrum of a high frequency part out of spectrum data obtained by converting an input acoustic signal for a constant time period, and outputs this parameter by matching this with encoded information of a low frequency part. Specifically, the encoding apparatus divides the spectrum data of a high frequency part of a frequency into plurality of sub-bands, and calculates a parameter that specifies a spectrum of a low frequency part that is most similar to the spectrum of each sub-band. Next, the encoding apparatus adjusts the most similar spectrum of a low frequency part by using two kinds of scaling factors such that a peak amplitude, or energy of a sub-band (hereinafter, “sub-band energy”) and a shape in a high-frequency spectrum to be generated becomes similar to a peak amplitude, sub-band energy, and a shape of a spectrum of a high frequency part of an input signal as a target.

CITATION LIST

Patent Literature

SUMMARY OF INVENTION

Technical Problem

However, according to the above-described Patent Literature 1, in combining a high-frequency spectrum, the encoding apparatus performs a logarithmic transform to all samples (MDCT coefficients) of spectrum data of an input signal and combined high-frequency spectrum data. Then, the encoding apparatus calculates a parameter such that respective sub-band energy and shapes becomes similar to a peak amplitude, sub-band energy, and a shape of a high-frequency spectrum of the input signal as the target. Therefore, there is a problem that the volume of arithmetic operations in the encoding apparatus is very large. Further, the encoding apparatus applies a calculated parameter to all samples within the sub-bands, and does not take into account sizes of amplitudes of individual samples. Consequently, the volume of arithmetic operations in the encoding apparatus when generating a high-frequency spectrum by using the calculated parameter also becomes very large. Further, quality of decoded speech to be generated is insufficient, and there is a possibility that abnormal sound is generated depending on the case.

It is therefore an object of the present invention to provide an encoding apparatus, a decoding apparatus and a method therefor capable of efficiently encoding spectrum data of a high frequency part and improving quality of a decoded signal based on spectrum data of a low frequency part of a broadband signal.

Solution to Problem

The encoding apparatus of the present invention is configured to include: first encoding means for generating first encoded information by encoding a lower frequency part equal to or lower than a predetermined frequency of an input signal; decoding means for generating a decoded signal by decoding the first encoded information; and second encoding means for generating second encoded information by dividing a high frequency part of the input signal higher than the predetermined frequency into a plurality of sub-bands, estimating the a plurality of sub-bands respectively from the input signal or the decoded signal, partially selecting a spectrum component within each of the sub-bands, and calculating an amplitude adjustment parameter for adjusting an amplitude for the selected spectrum component.

The decoding apparatus of the present invention is configured to include: receiving means for receiving first encoded information obtained by encoding a lower frequency part of an input signal equal to or lower than a predetermined frequency generated by the encoding apparatus, and second encoded information generated by dividing a high frequency part of the input signal higher than the predetermined frequency into a plurality of sub-bands, estimating the a plurality of sub-bands respectively from the input signal or from a first decoded signal obtained by decoding the first encoded information, partially selecting a spectrum component within each of the sub-bands, and calculating an amplitude adjustment parameter for adjusting an amplitude for the selected spectrum component; first decoding means for generating a second decoded signal by decoding the first encoded information; and second decoding means for generating a third decoded signal by estimating a high frequency part of the input signal from the second decoded signal.

The encoding method of the present invention includes: a step of generating first encoded information by encoding a lower frequency part of an input signal equal to or lower than a predetermined frequency; a step of generating a decoded signal by decoding the first encoded information; and a step of generating second encoded information by dividing a high frequency part of the input signal higher than the predetermined frequency into a plurality of sub-bands, estimating the a plurality of sub-hands respectively from the input signal or the decoded signal, partially selecting a spectrum component within each of the sub-bands, and calculating an amplitude adjustment parameter for adjusting an amplitude for the selected spectrum component.

The encoding method of the present invention includes: a step of receiving first encoded information obtained by encoding a lower frequency part of an input signal lower than a predetermined frequency generated by the encoding apparatus, and second encoded information generated by dividing a high frequency part of the input signal higher than the predetermined frequency into a plurality of sub-bands, estimating the a plurality of sub-bands respectively from the input signal or from a first decoded signal obtained by decoding the first encoded information, partially selecting a spectrum component within each of the sub-bands, and calculating an amplitude adjustment parameter for adjusting an amplitude for the selected spectrum component; a step of generating a second decoded signal by decoding the first encoded information; and a step of generating a third decoded signal by estimating a high frequency part of the input signal from the second decoded signal.

Advantageous Effects of Invention

According to the present invention, spectrum data of a high frequency part of a broadband signal can be efficiently encoded/decoded, the volume of arithmetic operations can be substantially reduced, and quality of a decoded signal can be also improved.

DESCRIPTION OF EMBODIMENTS

A main characteristic of the present invention is that the encoding apparatus calculates an adjustment parameter of sub-band energy and a shape of a sample group that is extracted based on a position of a sample of a maximum amplitude within a sub-band, when the encoding apparatus generates spectrum data of a high frequency part of a signal to be encoded based on spectrum data of a low frequency part. Another main characteristic is that the decoding apparatus applies the calculated parameter to the sample group that is extracted based on the position of the sample of a maximum amplitude within the sub-band. Based on these characteristics of the present invention, spectrum data of a high frequency part of a broadband signal can be efficiently encoded/decoded, the volume of arithmetic operations can be substantially reduced, and quality of a decoded signal can be also improved.

Embodiments of the present invention are explained in detail below with reference to drawings. A speech encoding apparatus and a speech decoding apparatus are explained as an example of the encoding apparatus and the decoding apparatus according to the present invention.

FIG. 1is a block diagram showing a configuration of a communication system that has an encoding apparatus and a decoding apparatus according to Embodiment 1 of the present invention. InFIG. 1, communication system includes encoding apparatus101and decoding apparatus103, and they can communicate with each other via transmission channel102. Both encoding apparatus101and decoding apparatus103are usually used by being mounted on a base station apparatus, a communication terminal device, or the like.

Encoding apparatus101divides an input signal into each N samples (N is a natural number), and encodes each frame by setting N samples as one frame. An input signal to be encoded is expressed as xn(n=0, . . . , N−1). This n denotes an (n+1)-th order of a signal element of the input signal that is divided into each N samples. Encoding apparatus101transmits encoded input information (encoded information) to decoding apparatus103via transmission channel102.

Decoding apparatus103receives encoded information transmitted from encoding apparatus101via transmission channel102.

FIG. 2is a block diagram showing a relevant configuration of the inside of encoding apparatus101shown inFIG. 1. When a sampling frequency of an input signal is SR1, down-sampling processing section201down-samples the sampling frequency of the input signal from SR1to SR2(SR2<SR1), and outputs the input signal that is down-sampled, to first layer encoding section202, as a down-sampled input signal. An operation is explained below by taking an example that SR2is a ½ sampling frequency of SR1.

First layer encoding section202generates first layer encoded information by encoding the down-sampled input signal that is input from down-sampling processing section201, by using a speech encoding method of a CELP (Code Excited Linear Prediction) system, for example. Specifically, first layer encoding section202generates the first layer encoded information, by encoding a lower frequency part of the input signal equal to or lower than a predetermined frequency. First layer encoding section202outputs the generated first layer encoded information to first layer decoding section203and encoded information multiplexing section207.

First layer decoding section203generates a first layer decoded signal by decoding the first layer encoded information that is input from first layer encoding section202, by using a speech decoding method of the CELP system, for example. First layer decoding section203outputs the generated first layer decoded signal to up-sampling processing section204.

Up-sampling processing section204up-samples from SR2to SR1a sampling frequency of the first layer decoded signal that is input from first layer decoding section203, and outputs the first layer decoded signal that is up-sampled, to orthogonal transform processing section205, as an up-sampled first layer decoded signal.

Orthogonal transform processing section205has buffers buf1n and buf2n (n=0, . . . , N−1) in the inside, and performs modified discrete cosine transformation (MDCT) to the input signal xn, and an up-sampled first layer decoded signal yn, that is input from up-sampling processing section204.

Regarding an orthogonal transform process by orthogonal transform processing section205, a calculation step and a data output to an internal buffer are explained below.

Next, orthogonal transform processing section205performs MDCT to the input signal xnand the up-sampled first layer decoded signal ynby following equations 3 and 4, and obtains an MDCT coefficient of the input signal (hereinafter, “input spectrum”) S2(k) and an MDCT coefficient of the up-sampled first layer decoded signal yr, (hereinafter, “first layer decoded spectrum”) S1(k).

In the above equations, k denotes an index of each sample in one frame. Orthogonal transform processing section205obtains x′nas a vector of combining the input signal xnand the buffer buf1nby following equation 5. Orthogonal transform processing section205also obtains yn′ as a vector of combining the up-sampled first layer decoded signal ynand the buffer buf2nby following equation 6.

Orthogonal transform processing section205outputs the input spectrum S2(k) and the first layer decoded spectrum S1(k) to second layer encoding section206.

The orthogonal transform process by orthogonal transform processing section205is explained above.

Second layer encoding section206generates second layer encoded information by using the input spectrum S2(k) and the first layer decoded spectrum S1(k) that are input from orthogonal transform processing section205, and outputs the generated second layer encoded information to encoded information multiplexing section207. A detail of second layer encoding section206is described later.

Encoded information multiplexing section207multiplexes the first layer encoded information that is input from first layer encoding section202and the second layer encoded information that is input from second layer encoding section206, and outputs a multiplexed information source code to transmission channel102as encoded information by adding a transmission error code or the like to this information source code when necessary.

A relevant configuration of the inside of second layer encoding section206shown inFIG. 2is explained next with reference toFIG. 3.

Second layer encoding section206includes band dividing section260, filter state setting section261, filtering section262, search section263, pitch coefficient setting section264, gain encoding section265, and multiplexing section266, and each section performs the following operation.

Band dividing section260divides a high frequency part (FL≦k<FH) of the input spectrum S2(k) that is input from orthogonal transform processing section205higher than a predetermined frequency into P (where P is an integer larger than 1) sub-bands SBp(p=0, 1, . . . , P−1). Band dividing section260outputs a bandwidth BWp(p=0, 1, . . . , P−1) and a header index (that is, a start position of a sub-band) BSp(p=0, 1, . . . , P−1) (FL≦BSp<FH) of each divided sub-band, as band division information, to filtering section262, search section263, and multiplexing section266. Hereinafter, out of the input spectrum S2(k), a part corresponding to the sub-band SBpis described as a sub-band spectrum S2p(k) (BSp≦k<BSp+BWp).

Filter state setting section261sets the first layer decoded spectrum S1(k) (0≦k<FL) that is input from orthogonal transform processing section205as a filter state to be used by filtering section262. That is, the first layer decoded spectrum S1(k) is stored as an internal state (a filter state), in a band of 0≦k<FL of the spectrum S(k) of an entire frequency band 0≦k<FH in filtering section262.

Filtering section262includes a pitch filter of multiple taps, filters the first layer decode spectrum based on a filter state that is set by filter state setting section261, a pitch coefficient that is input from pitch coefficient setting section264, and band division information that is input from band dividing section260, and calculates an estimated value S2p′(k) (BSp≦k<BSp+BWp) (p=0, 1, . . . , P−1) (hereinafter, “estimated spectrum S2p′ of sub-band SBp) of each sub-band SBp(p=0, 1, . . . , P−1). Filtering section262outputs the estimated spectrum S2p′(k) of the sub-band SBpto search section263. A detail of the filtering process of filtering section262is described later. It is assumed that the number of taps of multiple taps can be an arbitrary value (an integer) equal to or larger than 1.

Search section263calculates a degree of similarity between the estimated spectrum S2p′(k) of the sub-band SBpthat is input from filtering section262and the spectrum S2p(k) of each sub-band in the high frequency part (FL≦k<FH) of the input spectrum S2(k) that is input from orthogonal transform processing section205, based on the band division information that is input from band dividing section260. This degree of similarity is calculated by a correlation calculation, for example. Processes of filtering section262, search section263, and pitch coefficient setting section264constitute a search process of a closed loop for each sub-band. In each closed loop, search section263calculates a degree of similarity corresponding to each pitch coefficient by variously changing a pitch coefficient T that is input from pitch coefficient setting section264to filtering section262. In a closed loop for each sub-band, search section263obtains an optimal pitch coefficient Tp′ (within a range of Tmin to Tmax) at which the degree of similarity becomes maximum in a closed loop corresponding to the sub-band SBp, and outputs P optimal pitch coefficients to multiplexing section266. A detail of a calculation method of a degree of similarity by search section263is described later.

Search section263calculates a part of the band (a band that is most similar to each spectrum of each sub-band) of the first layer decoded spectrum similar to each sub-band SBp, by using each optimal pitch coefficient Tp′. Further, search section263outputs to gain encoding section265the estimated spectrum S2p′(k) corresponding to each optimal pitch coefficient Tp′ (p=0, 1, . . . , P−1), and an ideal gain α1p, as an amplitude adjustment parameter that is used to calculate the optimal pitch coefficient Tp′ (p=0, 1, . . . , P−1) calculated following equation 9. In equation 9, M′ denotes the number of samples to use to calculate a degree of similarity D, and this can be an arbitrary value equal to or smaller than a bandwidth of each sub-band. Needless to mention, M′ can be a value of a sub-band width BWi. A detail of the search process of the optimal pitch coefficient Tp′ (p=0, 1, . . . , P−1) by search section263is described later.

Pitch coefficient setting section264sequentially outputs to filtering section262the pitch coefficient T by slightly changing it in a predetermined search range Tmin to Tmax together with filtering section262and search section263under the control of search section263. Pitch coefficient setting section264can set the pitch coefficient T by slightly changing it in the predetermined search range Tmin to Tmax in the case of performing a search process of a closed loop corresponding to the first sub-band, and can set the pitch coefficient T by slightly changing it based on an optimal pitch coefficient obtained in a search process of a closed loop corresponding to the (m−1)-th sub-band in the case of performing a search process of a closed loop corresponding to the m-th (m=2, 3, . . . , P) sub-band at and after a second sub-band, for example.

Gain encoding section265calculates for each sub-band, a logarithmic gain as a parameter for adjusting an energy ratio in a nonlinear domain, based on the input spectrum S2(k), and the estimated spectrum S2p′(k) (p=0, 1, . . . , P−1) and the deal gain α1pof each sub-band that are input from search section263. Gain encoding section265quantizes the ideal gain and the logarithmic gain, and outputs the quantized ideal gain and the quantized logarithmic gain to multiplexing section266.

FIG. 4shows an internal configuration of gain encoding section265. Gain encoding section265is mainly comprised of ideal gain encoding section271and logarithmic gain encoding section272.

Ideal gain encoding section271configures the estimated spectrum S2′ (k) of the high frequency part of the input spectrum by continuing in the frequency part the estimated spectrum S2p′(k) (p=0, 1, . . . , P−1) of each sub-band that is input from search section263. Next, ideal gain encoding section271calculates an estimated spectrum S3′(k) by multiplying the ideal gain α1pof each sub-band input from search section263to the estimated spectrum S2′ (k) following an equation 10. In the equation 10, BLpdenotes a header index of each sub-band, and BHpdenotes an end index of each sub-band. Ideal gain encoding section271outputs the calculated estimated spectrum S3′(k) to logarithmic gain encoding section272. Ideal gain encoding section271quantizes the ideal gain α1p, and outputs a quantized ideal gain αQ1pto multiplexing section266as ideal gain encoded information.
Equation 10
S3′(k)=S2′(k)·α1p(BLp≦k≦BHp, for allp)  [10]

Logarithmic gain encoding section272calculates a logarithmic gain as a parameter (an amplitude adjustment parameter) for adjusting an energy ratio in the nonlinear domain for each sub-band between the high frequency part (FL≦k<FH) of the input spectrum S2(k) that is input from orthogonal transform processing section205and the estimated spectrum S3′(k) that is input from ideal gain encoding section271. Logarithmic gain encoding section272outputs the calculated logarithmic gain to multiplexing section266as logarithmic gain encoded information.

FIG. 5shows an internal configuration of logarithmic gain encoding section272. Logarithmic gain encoding section272is mainly comprised of maximum amplitude value search section281, sample group extracting section282, and logarithmic gain calculating section283.

Maximum amplitude value search section281searches for, for each sub-band, a maximum amplitude value MaxValuep, and an index of a sample (a spectrum component) of a sample of a maximum amplitude, that is, a maximum amplitude index MaxIndexp, for the estimated spectrum S3′(k) that is input from ideal gain encoding section271, as expressed by equation 11.

Sample group extracting section282determines an extraction flag SelectFlag(k) for each sample corresponding to the calculated maximum amplitude index MaxIndexpfor each sub-band, as expressed by equation 12. Sample group extracting section282outputs the estimated spectrum S3′(k), the maximum amplitude value MaxValuep, and the extraction flag SelectFlag(k) to logarithmic gain calculating section283. In the equation 12, Nearpdenotes a threshold value that becomes a basis of determining the extraction flag SelectFlag(k).

That is, sample group extracting section282determines a value of the extraction flag SelectFlag(k) based on a standard that the value of the extraction flag SelectFlag(k) easily becomes 1 for a sample (a spectrum component) that is nearer a sample having the maximum amplitude value MaxValuepin each sub-band, as expressed by equation 12. That is, sample group extracting section282partially selects a sample based on a weight that enables a sample to be easily selected that is nearer a sample having the maximum amplitude value MaxValuepin each sub-band. Specifically, sample group extracting section282selects a sample of an index that indicates that a distance from the maximum amplitude value MaxValuepis within a range of Nearp, as expressed by equation 12. Further, sample group extracting section282sets a value of the extraction flag SelectFlag(k) to 1 for a sample of an even-numbered index even when the sample is not near a sample having a maximum amplitude value, as expressed by equation 12. Accordingly, even when a sample having a large amplitude is present in a band far from a sample having a maximum amplitude value, this sample or a sample having an amplitude near the amplitude of this sample can be extracted.

Logarithmic gain calculating section283calculates an energy ratio (a logarithmic gain) α1pin a logarithmic domain of the high frequency part (FL≦k<FH) of the estimated spectrum S3′(k) and the input spectrum S2(k), following equation 13, for a sample where the value of the extraction flag SelectFlag(k) that is input from sample group extracting section282is 1. In equation 13, M′ denotes the number of samples to use to calculate a logarithmic gain, and this can be an arbitrary value equal to or smaller than a bandwidth of each sub-band. Needless to mention, M′ can be a value of a sub-band width BWi.

That is logarithmic gain calculating section283calculates the logarithmic gain α2pfor only a sample that is partially selected by sample group extracting section282. Logarithmic gain calculating section283quantizes the logarithmic gain α2p, and outputs a quantized logarithmic gain α2Qpto multiplexing section266as logarithmic gain encoded information.

The process by gain encoding section265is explained above.

Multiplexing section266multiplexes, as second layer encoded information, the band division information that is input from band dividing section260, the optimal pitch coefficient Tp′ to each sub-band SBp(p=0, 1, . . . , P−1) that is input from search section263, the indexes (the ideal gain encoded information and the logarithmic gain encoded information) respectively corresponding to the ideal gains α1Qpand the logarithmic gain α2Qpthat are input from gain encoding section265, and outputs the second layer encoded information to encoded information multiplexing section207. The indexes of Tp′, and α1Qpand α2Qpcan be directly input to encoded information multiplexing section207, and can be multiplexed as the first layer encoded information by encoded information multiplexing section207.

A detail of the filtering process by filtering section262shown inFIG. 3is explained next with reference toFIG. 6.

Filtering section262generates an estimated spectrum in a band BSp≦k<BSp+BWp(p=0, 1, . . . , P−1) for the sub-band SBp(p=0, 1, . . . , P−1), by using the filter state that is input from filter state setting section261, the pitch coefficient T that is input from pitch coefficient setting section264, and the band division information that is input from band dividing section260. A transmission function F(z) of a filter that is used by filtering section262is expressed by following equation 14.

A process of generating the estimated spectrum S2p′(k) of the sub-band spectrum S2p(k) is explained next by taking the sub-band SBpas an example.

In equation 14, T denotes a pitch coefficient that is given from pitch coefficient setting section264, and βidenotes a filter coefficient that is stored beforehand in the inside. For example, when the number of taps is 3, a candidate of the filter coefficient is (β−1, β0, β1)=(0.1, 0.8, 0.1). Further, a value of (β−1, β0, β1)=(0.2, 0.6, 0.2), (0.3, 0.4, 0.3) is also suitable. A value of (β−1, β0, β1)=(0.0, 1.0, 0.0) is also suitable, and in this case, the value indicates that a part of a band of the first layer decoded spectrum of the band 0≦k<FL is directly copied to the band of BSp≦k<BSp+BWpwithout changing a shape of the part of the band. In the following explanation, the value of (β−1, β0, β1)=(0.0, 1.0, 0.0) is assumed as an example. In equation 14, it is assumed that M=1. M denotes an index that is relevant to the number of taps.

The first layer decoded spectrum S1(k) is stored as an internal state (a filter state), in the band of 0≦k<FL of the spectrum S(k) of the entire frequency band in filtering section262.

The estimated spectrum S2p′(k) of the sub-band SBpis stored in the band of BSp≦k<BSp+BWpof S(k), by a filtering process in the following step. That is, as shown inFIG. 6, basically, a spectrum S(k−T) of a frequency that is lower than k by T is substituted in S2p′(k). However, to increase smoothness of the spectrum, actually, a spectrum that is obtained by adding to all i, a spectrum βi·S(k−T+i) obtained by multiplying a near spectrum S(k−T+1) that is far by only i from the spectrum S(k) by a predetermined filter coefficient βi, is substituted in S2p′(k). This process is expressed by following equation 15.

The estimated spectrum S2p′(k) in BSp≦k<BSp+BWpis calculated by performing the above calculation, sequentially from k=BSpof a low frequency, by changing k in the range of BSp≦k<BSp+BWp.

The above filtering process is performed by zero-clearing S(k) each time in the range of BSp≦k<BSp+BWp, each time when the pitch coefficient T is given from pitch coefficient setting section264. That is S(k) is calculated each time when the pitch coefficient T changes, and a result is output to search section263.

FIG. 7is a flowchart showing a step of a process of searching for an optimal pitch coefficient TP′ of a sub-band SBPin search section263shown inFIG. 3. Search section263searches for the optimal pitch coefficient TP′ (p=0, 1, . . . , P−1) corresponding to each sub-band SBp(p=0, 1, . . . , P−1), by repeating the step shown inFIG. 7.

First, search section263initializes a minimum degree of similarity Dmin, as a variable to store a minimum value of a degree of similarity, to “+∞” (ST2010). Next, search section263calculates a degree of similarity D between the high frequency part (FL≦k<FH) of the input spectrum S2(k) in a certain pitch coefficient and the estimated spectrum S2p′(k), based on following equation 16 (ST2020).

In equation 16, M′ denotes the number of samples to calculate a degree of similarity D, and this value can be an arbitrary value equal to or smaller than a bandwidth of each sub-band. Needless to mention, M′ can take a value of the sub-band width BWi. In equation 16, S2p′(k) is not present, because BSpand S2′(k) are used to represent S2p′(k).

Search section263determines whether the calculated degree of similarity D is smaller than the minimum degree of similarity Dmin(ST2030). When the degree of similarity D calculated at ST2020 is smaller than the minimum degree of similarity Dmin(YES in ST2030), search section263substitutes the degree of similarity D to the minimum degree of similarity Dmin(ST2040). On the other hand, when the degree of similarity calculated at ST2020 is equal to or larger than the minimum degree of similarity Dmin(NO in ST2030), search section determines whether a process in the search range is finished. That is, search section263determines whether a degree of similarity has been calculated to all pitch coefficients within the search range following above equation 16 at ST2020 (ST2050). When the process is not finished in the search range (NO in ST2050), search section263returns the process to ST2020. Search section calculates a degree of similarity following equation 16 to pitch coefficients that are different from pitch coefficient to which a degree of freedom is calculated following equation 16 in the last step of ST2020. On the other hand, when the process is finished in the search range (YES in ST2050), search section263outputs the pitch coefficient T corresponding to the minimum degree of similarity Dminto multiplexing section266as an optimal pitch coefficient Tp′ (ST2060).

FIG. 8is a block diagram showing a relevant configuration of the inside of decoding apparatus103.

InFIG. 8, encoded information demultiplexing section131demultiplexes the first layer encoded information and the second layer encoded information from among the input encoded information (that is, the encoded information received from encoding apparatus101), outputs the first layer encoded information to first layer decoding section132, and outputs the second layer encoded information to second layer decoding section135.

First layer decoding section132decodes the first layer encoded information that is input from encoded information demultiplexing section131, and outputs a generated first layer decoded signal to up-sampling processing section133. Operation of first layer decoding section132is similar to that of first layer decoding section203shown inFIG. 2, and therefore, a detailed explanation of the operation is omitted.

Up-sampling processing section133performs a process of up-sampling a sampling frequency from SR2to SR1to the first layer decoded signal that is input from first layer decoding section132, and outputs an obtained up-sampled first layer decoded signal to orthogonal transform processing section134.

Orthogonal transform processing section134performs an orthogonal transform process (MDCT) to the up-sampled first layer decoded signal that is input from up-sampling processing section133, and outputs an MDCT coefficient of the obtained up-sampled first layer decoded signal (hereinafter, “first layer decoded spectrum”) S1(k) to second layer decoding section135. Operation of orthogonal transform processing section134is similar to that of orthogonal transform processing section205shown inFIG. 2performed to the up-sampled first layer decoded signal, and therefore, a detailed explanation of the operation is omitted.

Second layer decoding section135generates the second layer decoded signal containing a high frequency component, by using the first layer decoded spectrum S1(k) that is input from orthogonal transform processing section134and the second layer encoded information that is input from encoded information demultiplexing section131, and outputs the generated signal as an output signal.

FIG. 9is a block diagram showing a relevant configuration of the inside of second layer decoding section shown inFIG. 8.

Demultiplexing section351demultiplexes the second layer encoded information that is input from encoded information demultiplexing section131, into the band division information that contains the bandwidth BWp(p=0, 1, . . . , P−1) and the header index BSp(p=0, 1, . . . , P−1) (FL≦BSp<FH) of each sub-band, the optimal pitch coefficient TP′ (p=0, 1, . . . , P−1) as information concerning filtering, and indexes of ideal gain encoded information (j=0, 1, . . . , J−1) and logarithmic gain encoded information (j=0, 1, . . . , J−1) as information concerning gain. Demultiplexing section351outputs the band division information and the optimal pitch coefficient Tp′ (p=0, 1, . . . , P−1) to filtering section353, and outputs the indexes of the ideal gain encoded information and the logarithmic gain encoded information to gain decoding section354. In encoded information demultiplexing section131, when the second layer encoded information is already divided into the band division information, the optimal pitch coefficient TP′ (p=0, 1, . . . , P−1), and the indexes of ideal gain encoded information and logarithmic gain encoded information, demultiplexing section351does not need to be arranged.

Filter state setting section352sets the first layer decoded spectrum S1(k) (0≦k<FL) that is input from orthogonal transform processing section134, as a filter state to be used by filtering section353. When the spectrum of the entire frequency band 0≦k<FH in filtering section353is called S(k) for convenience, the first layer decoded spectrum S1(k) is stored in the band of 0≦k<FL of S(k) as an internal state (a filter state) of the filter. A configuration and operation of filter state setting section352are similar to those of filter state setting section261shown inFIG. 3, and therefore, a detailed explanation the configuration and operation is omitted.

Filtering section353includes a pitch filter of a multi-tap (the number of taps is larger than 1). Filtering section353filters the first layer decoded spectrum S1(k), and calculates the estimated value S2p′(k) (BSp≦k<BSp+BWp) (p=0, 1, . . . , P−1) of each sub-band SBp(p=0, 1, . . . , P−1) shown in above equation 15, based on the band division information that is input from demultiplexing section351, the filter state that is set by filter state setting section352, pitch coefficient Tp′ (p=0, 1, . . . , p−1) and the filter coefficient stored in the inside beforehand. A filter function shown in above equation 14 is also used in filtering section353. However, the filtering process and the filter function in this case are different in that T in equations 14 and 15 are substituted to Tp′. That is, filtering section353estimates a high frequency part of the input spectrum in encoding apparatus101from the first layer decoded spectrum.

Gain decoding section354decodes the indexes of the ideal gain encoded information and logarithmic gain encoded information that are input from demultiplexing section351, and obtains the quantized ideal gain αQ1pand the quantized logarithmic gain α2Qpof the quantized values of the ideal gain α1pand the logarithmic gain α2p.

Spectrum adjusting section355calculates a decoded spectrum, based on the estimated value S2p′(k) (BSp≦k<BSp+BWp) (p=0, 1, . . . , P−1) of each sub-band SBp(p=0, 1, . . . , P−1) that is input from filtering section353, and the ideal gain αQ1pfor each sub-band that is input from gain decoding section354. Spectrum adjusting section355outputs the calculated decoded spectrum to orthogonal transform processing section356.

FIG. 10shows an internal configuration of spectrum adjusting section355. Spectrum adjusting section355is mainly comprised of ideal gain decoding section361and logarithmic gain decoding section362.

Ideal gain decoding section361obtains the estimated spectrum S2′(k) of the input spectrum, by continuing in a frequency part the estimated value S2p′(k) (BSp≦k<BSp+BWp) (p=0, 1, . . . , P−1) of each sub-band that is input from filtering section353. Next, ideal gain decoding section361calculates the estimated spectrum S3′(k) by multiplying the deal gain αQ1pfor each sub-band that is input from gain decoding section354to the estimated spectrum S2′(k), based on following equation 17. Ideal gain decoding section361outputs the estimated spectrum S3′(k) to logarithmic gain decoding section362.
Equation 17
S3′(k)=S2′(k)·α1Qp(BLp≦k≦BHp, for allp)  [17]

Logarithmic gain decoding section362performs energy adjustment in the logarithmic domain to the estimated spectrum S3′(k) that is input from ideal gain decoding section361, by using the quantized logarithmic gain α2Qpfor each sub-band that is input from gain decoding section354, and outputs an obtained spectrum to orthogonal transform processing section356as a decoded spectrum.

FIG. 11shows an internal configuration of logarithmic gain decoding section362. Logarithmic gain decoding section362is mainly comprised of maximum amplitude value search section371, sample group extracting section372, and logarithmic gain applying section373.

Maximum amplitude value search section371searches for, for each sub-band, the maximum amplitude value MaxValuep, and the maximum amplitude index MaxIndexpas the index of the sample (a sample component) of a maximum amplitude, to the estimated spectrum S3′(k) that is input from ideal gain decoding section361, as expressed by equation 11. Maximum amplitude value search section371outputs the estimated spectrum S3′(k), the maximum amplitude value MaxValuep, and the maximum amplitude index MaxIndexp, to sample group extracting section372.

Sample group extracting section372determines the extraction flag SelectFlag(k) for each sample, corresponding to the calculated maximum amplitude index MaxIndexpfor each sub-band, as expressed by equation 12. That is, sample group extracting section372partially selects a sample, based on a weight that enables a sample (a spectrum component) to be easily selected that is nearer a sample having the maximum amplitude value MaxValuepin each sub-band. Sample group extracting section372outputs the estimated spectrum S3′(k), the maximum amplitude value MaxValuep, and the maximum amplitude index MaxIndexpand the extraction flag SelectFlag(k) for each sample, to logarithmic gain applying section373.

Processes performed by maximum amplitude value search section371and sample group extracting section372are similar to processes performed by maximum amplitude value search section281and sample group extracting section282of encoding apparatus101.

Logarithmic gain applying section373calculates Signp(k) that indicates a sign (+, −) of an extracted sample group, from the estimated spectrum S3′(k) and the extraction flag SelectFlag(k) that are input from sample group extracting section372, as expressed by equation 18. That is, as expressed by equation 18, logarithmic gain applying section373calculates Signp(k)=1 when the sign of the extracted sample is “+” (when S3′(k)≧0), and calculates Signp(k)=−1 in other cases (when the sign of the extracted sample is “−” (when Signp(k)≧0).

Logarithmic gain applying section373calculates a decoded spectrum S5′(k), following equations 19 and 20, for a sample where the value of the extraction flag SelectFlag(k) is 1, based on the estimated spectrum S3′(k), the maximum amplitude value MaxValuep, and the extraction flag SelectFlag(k) that are input from sample group extracting section372, and based on the quantized logarithmic gain α2Qpthat is input from gain decoding section354, and the sign Signp(k) that is calculated following equation 18.

That is, logarithmic gain applying section373applies the logarithmic gain α2pto only a sample that is partially selected by sample extracting section372(a sample of the extraction flag SelectFlag(k=1). Logarithmic gain applying section373outputs the decoded spectrum S5′(k) to orthogonal transform processing section356. In this case, a low frequency part (0≦k<FL) of the decoded spectrum S5′(k) is comprised of the first layer decoded spectrum S1(k), and a high frequency part (FL≦k<FH) of the decoded spectrum S5′(k) is comprised of the spectrum obtained by performing energy adjustment in the logarithmic domain to the estimated spectrum S3′(k). However, for a sample that is not selected by sample extracting section372(a sample of the extraction flag SelectFlag(k)=0), in the high frequency part (FL≦k<FH) of the decoded spectrum S5′(k), a value of this sample is set as the value of the estimated spectrum S3′(k).

Orthogonal transform processing section356orthogonally converts the decoded spectrum. S5′(k) that is input from spectrum adjusting section355into a signal of a time domain, and outputs an obtained second layer decoded signal as an output signal. In this case, proper windowing and superimposition addition processes are performed when necessary, thereby avoiding discontinuity generated between frames.

A detailed process of orthogonal transform processing section356is explained below.

Orthogonal transform processing section356has a buffer buf′(k) in its inside, and initializes the buffer buf′(k) as expressed by following equation 21.
Equation 21
buf′(k)=0=0(k=0, . . . , N−1)  [21]

Orthogonal transform processing section356also obtains a second layer decoded signal yn″, based on following equation 22 by using the second layer decoded spectrum S5′(k) that is input from spectrum adjusting section355.

In equation 22, Z4(k) is vector that combines the decoded spectrum S5′(k) and the buffer buf′(k), as expressed by following equation 23.

Orthogonal transform processing section356outputs the decoded signal yn″ as an output signal.

As explained above, according to the present embodiment, in the encoding/decoding for estimating a spectrum of a high frequency part by performing a band expansion by using a spectrum of a low frequency part, the spectrum of the high frequency part is estimated by using a decoded low frequency spectrum, and thereafter, a sample is selected (thinned) by placing a weight on a sample at the periphery of a maximum amplitude value in each sub-band of the estimated spectrum, and a gain adjustment in the logarithmic domain is performed for only the selected sample. Based on this configuration, the volume of arithmetic operations necessary for the gain adjustment in the logarithmic domain can be substantially reduced. Further, by performing a gain adjustment to only an acoustically important sample near the maximum amplitude value, generation of abnormal sound which results in amplification of a sample of a low amplitude value can be suppressed, and sound quality of a decoded signal can be improved.

In the present embodiment, in the setting of an extraction flag, a value of the extraction flag is set to 1 when the index is an even number, for a sample which is not near the sample having a maximum amplitude value within a sub-band. However, application of the present invention is not limited to this, and the invention can be similarly applied to the case where a value of an extraction flag of a sample in which a surplus to the index 3 is 0 is set to 1, for example. That is, application of the present invention is not limited to the above setting method of an extraction flag, and the present invention can be similarly applied to a method of extracting a sample based on a weight (a scale) that enables a value of an extraction flag to be easily set to 1 for a sample that is nearer a sample having the maximum amplitude value, corresponding to a position of the maximum amplitude value within a sub-band. For example, there is a setting method of an extraction flag in three step that the encoding apparatus and the decoding apparatus extract all samples that are very near a sample having the maximum amplitude value (that is, the encoding apparatus and the decoding apparatus set a value of the extraction flag to 1), extract samples that are slightly far from the maximum amplitude value only when the index is an even number, and extract samples that are farther from the maximum amplitude value when a surplus to the index 3 is 0. Needless to mention, the present invention can be also applied to a setting method in more than three steps.

In the present embodiment, in the setting of an extraction flag, it is explained as an example that after a sample that has a maximum amplitude value within a sub-band is searched for, an extraction flag is set corresponding to a distance from this sample. However, application of the present embodiment is not limited to this, and the invention can be also applied to the case where the encoding apparatus and the decoding apparatus search for a sample that has a minimum amplitude value, set an extraction flag of each sample corresponding to a distance from the sample that has a minimum amplitude value, and calculate and apply an amplitude adjustment parameter of a logarithmic gain and the like to only the extracted sample (the sample where the value of an extraction flag is set to 1), for example. This configuration is valid when the amplitude adjustment parameter has an effect of attenuating the estimated high frequency spectrum, for example. Although there is a risk of generating abnormal sound by attenuating the high frequency spectrum to a sample having a large amplitude, there is a possibility of improving the sound quality by applying an attenuation process to only the periphery of the sample having the minimum amplitude value. There is also a configuration that the encoding apparatus and the decoding apparatus extract a sample by using a weight (a scale) that enables a sample to be easily extracted that is farther from a sample having a maximum amplitude value by searching for the maximum amplitude value, instead of searching for a minimum amplitude value. The present invention can be also similarly applied to this configuration.

In the present embodiment, in the setting of an extraction flag, it is explained as an example that after a sample that has a maximum amplitude value within a sub-band is searched for, an extraction flag is set corresponding to a distance from this sample. However, application of the present embodiment is not limited to this, and the invention can be similarly applied to the case where a sample flag is set to a plurality of samples corresponding to a distance from each sample, by selecting these samples from samples having a larger amplitude, for each sub-band. By providing the above configuration, a sample can be efficiently extracted, when a plurality of samples that have near sizes of amplitudes are present within a sub-band.

In the present embodiment, the case is explained where a sample is partially selected by determining whether a sample within each sub-band is near a sample that has a maximum amplitude value, based on a threshold value (Nearpexpressed in equation 12). In the present invention, the encoding apparatus and the decoding apparatus can be arranged to select a sample of a broader range for a sub-band in a higher frequency among a plurality of sub-bands, as a sample that is near the sample having a maximum amplitude value, for example. That is, in the present invention, Nearpthat is expressed in equation 12 can take a larger value for a sub-band of a higher frequency among a plurality of sub-bands. With this arrangement, at a band division time, even when a sub-band width is set to be larger for a higher frequency like a Bark scale, for example, a sample can be partially selected without deviation between sub-bands, and degradation of sound quality of a decoded signal can be prevented. It is experimentally confirmed that, for a value of Nearpthat is expressed by equation 12, a good result is obtained by setting about 5 to 21 (for example, a value of Nearpin a lowest frequency sub-band is 5, and a value of Nearpin a highest frequency sub-band is 21) when the number of samples (MDCT coefficients) of one frame is about 320, for example.

In the present embodiment, a configuration of the encoding apparatus and the decoding apparatus is explained that the sample group detecting section partially selects a sample based on a weight that enables a sample to be easily selected that is nearer a sample having the maximum amplitude value MaxValuepin each sub-band, as expressed by equation 12. In this case, by a sample group extracting method that is expressed by equation 12, a sample near the maximum amplitude value can be easily selected, regardless of a boundary of a sub-band, even when a sample having the maximum amplitude value is present in the boundary of each sub-band. That is, according to the configuration explained in the present embodiment, because a sample is selected by considering a position of a sample that has the maximum amplitude value within an adjacent sub-band, an acoustically important sample can be efficiently selected.

In the present embodiment, the maximum amplitude value search section calculates a maximum amplitude in a linear domain not in a logarithmic domain. When a logarithmic transform is performed to all samples (the MDCT coefficients) (for example, Patent Literature 1 and the like), the volume of arithmetic operations does not increase so much when a maximum amplitude value is calculated in the logarithmic domain or in the linear domain. However, like in the configuration of the present embodiment, when a logarithmic transform is performed to a partially selected sample, the volume of arithmetic operations when calculating a maximum amplitude value can be reduced more than that by a method in Patent Literature 1 and the like, for example, when the maximum amplitude value search section calculates the maximum amplitude value in the linear domain as described above.

In Embodiment 2 of the present invention, a gain encoding section within the second layer encoding section can further reduce the volume of arithmetic operations by using a configuration which is different from the configuration explained in Embodiment 1.

A communication system (not shown) according to Embodiment 2 is basically similar to the communication system shown inFIG. 1, and is different from encoding apparatus101and decoding apparatus103of the communication system inFIG. 1in only a part of a configuration and operation of the encoding apparatus and the decoding apparatus. Embodiment 2 is explained below by adding reference numbers111and113respectively to the encoding apparatus and the decoding apparatus according to the present embodiment.

The inside of encoding apparatus111(not shown) according to the present embodiment is mainly comprised of down-sampling processing section201, first layer encoding section202, first layer decoding section203, up-sampling processing section204, orthogonal transform processing section205, second layer encoding section206, and encoded information multiplexing section207. Constituent elements other than second layer encoding section226perform the same processes as those in Embodiment 1 (FIG. 2), and therefore, their explanation is omitted.

Second layer encoding section226generates the second layer encoded information by using the input spectrum S2(k) and the first layer decoded spectrum S1(k) that are input from orthogonal transform processing section205, and outputs the generated second layer encoded information to encoded information multiplexing section207.

Next, a relevant configuration of the inside of second layer encoding section226is explained with reference toFIG. 12.

Second layer encoding section206includes band dividing section260, filter state setting section261, filtering section262, search section263, pitch coefficient setting section264, gain encoding section235, and multiplexing section266, and each section performs the following operation. Constituent elements other than gain encoding section235are the same as the constituent elements explained in Embodiment 1 (FIG. 3), and therefore, their explanation is omitted.

Gain encoding section235calculates for each sub-band, a logarithmic gain as a parameter (an amplitude adjustment parameter) for adjusting an energy ratio in a nonlinear domain, based on the input spectrum S2(k), and the estimated spectrum S2p′(k) (p=0, 1, . . . , P−1) and the deal gain α1pof each sub-band that are input from search section263. Gain encoding section235quantizes the ideal gain and the logarithmic gain, and outputs the quantized ideal gain and the quantized logarithmic gain to multiplexing section266.

FIG. 13shows an internal configuration of gain encoding section235. Gain encoding section235is mainly comprised of ideal gain encoding section241and logarithmic gain encoding section242. Ideal gain encoding section241is the same constituent element as that explained in Embodiment 1, and therefore explanation of ideal gain encoding section241is omitted.

Logarithmic gain encoding section242calculates a logarithmic gain as a parameter (an amplitude adjustment parameter) for adjusting an energy ratio in the nonlinear domain for each sub-band between the high frequency part (FL≦k<FH) of the input spectrum S2(k) that is input from orthogonal transform processing section205and the estimated spectrum S3′(k) that is input from ideal gain encoding section241. Logarithmic gain encoding section242outputs the calculated logarithmic gain to multiplexing section266as logarithmic gain encoded information.

FIG. 14shows an internal configuration of logarithmic gain encoding section242. Logarithmic gain encoding section242is mainly comprised of maximum amplitude value search section253, sample group extracting section251, and logarithmic gain calculating section252.

Maximum amplitude value search section253searches for, for each sub-band, a maximum amplitude value MaxValuep, and an index of a sample (a spectrum component) of a maximum amplitude, that is, a maximum amplitude index MaxIndexp, for the estimated spectrum S3′(k) that is input from ideal gain encoding section241, as expressed by equation 25.

That is, maximum amplitude value search section253searches for a maximum amplitude value for only a sample of an even-numbered index. With this arrangement, the volume of arithmetic operations required to search for a maximum amplitude value can be efficiently reduced.

Sample group extracting section251determines a value of an extraction flag SelectFlag(k) for each sample (a spectrum component) to the estimated spectrum S3′(k) that is input from maximum amplitude value search section253, based on following equation 26.

That is, sample group extracting section251sets a value of the extraction flag SelectFlag(k) to 0 for a sample of an odd-numbered index, and sets a value of the extraction flag SelectFlag(k) to 1 for a sample of an even-numbered index, as expressed by equation 26. That is, sample group extracting section251partially selects a sample (a spectrum component) (only the sample of the index of an even number), to the estimated spectrum S3′(k). Sample group extracting section251outputs the extraction flag SelectFlag(k), the estimated spectrum S3′(k), and the maximum amplitude value MaxValuepto logarithmic gain calculating section252.

Logarithmic gain calculating section252calculates an energy ratio (a logarithmic gain) α2pin a logarithmic domain between the estimated spectrum S3′(k) and the high frequency part (FL≦k<FH) of the input spectrum S2(k), based on the equation 13, for a sample where the value of the extraction flag SelectFlag(k) that is input from sample group extracting section251is 1. That is, logarithmic gain calculating section252calculates the logarithmic gain α2pfor only a sample that is partially selected by sample group extracting section251.

Logarithmic gain calculating section252quantizes the logarithmic gain α2p, and outputs a quantized logarithmic gain α2Qpto multiplexing section266as logarithmic gain encoded information.

The process by gain encoding section235is explained above.

The process of encoding apparatus111according to the present embodiment is as explained above.

On the other hand, the inside of decoding apparatus113(not shown) according to the present embodiment is mainly comprised of encoded information demultiplexing section131, first layer decoding section132, up-sampling processing section133, orthogonal transform processing section134, and second layer decoding section295. Constituent elements other than second layer decoding section295perform the same processes as those in Embodiment 1 (FIG. 8), and therefore, their explanation is omitted.

Second layer decoding section295generates the second layer decoded signal containing a high frequency component, by using the first layer decoded spectrum S1(k) that is input from orthogonal transform processing section134and the second layer encoded information that is input from encoded information demultiplexing section131, and outputs the generated signal as an output signal.

Second layer decoding section295is mainly comprised of demultiplexing section351, filter state setting section352, filtering section353, gain decoding section354, spectrum adjusting section396, and orthogonal transform processing section356. Constituent elements other than spectrum adjusting section396perform the same processes as those in Embodiment 1 (FIG. 9), and therefore, their explanation is omitted.

Spectrum adjusting section396is mainly comprised of ideal gain decoding section361and logarithmic gain decoding section392(not shown). Ideal gain decoding section361performs the same process as that in Embodiment 1 (FIG. 10), and therefore, explanation of ideal gain decoding section361is omitted.

FIG. 15shows an internal configuration of logarithmic gain decoding section392. Logarithmic gain encoding section392is mainly comprised of maximum amplitude value search section381, sample group extracting section382, and logarithmic gain applying section383.

Maximum amplitude value search section381searches for, for each sub-band, a maximum amplitude value MaxValuep, and an index of a sample (a spectrum component) of a sample of a maximum amplitude, that is, a maximum amplitude index MaxIndexp, for the estimated spectrum S3′(k) that is input from ideal gain decoding section361, as expressed by equation 25. That is, maximum amplitude value search section381searches for a maximum amplitude value for only a sample of an even-numbered index. That is, maximum amplitude value search section381searches for a maximum amplitude value for only a part of a sample (a spectrum component) out of the estimated spectrum S3′(k). With this arrangement, the volume of arithmetic operations required to search for a maximum amplitude value can be efficiently reduced. Maximum amplitude value search section381outputs the estimated spectrum S3′(k), the maximum amplitude value MaxValuep, and the maximum amplitude index MaxIndexpto sample group extracting section382.

Sample group extracting section382determines the extraction flag SelectFlag(k) for each sample, corresponding to the calculated maximum amplitude index Maxindexpfor each sub-band, as expressed by equation 12. That is, sample group extracting section382partially selects a sample, based on a weight that enables a sample (a spectrum component) to be easily selected that is nearer a sample having the maximum amplitude value MaxValuepin each sub-band. Specifically, sample group extracting section382selects a sample of an index that indicates that a distance from the maximum amplitude value MaxValuepis within a range of Nearp, as expressed by equation 12. Further, sample group extracting section382sets a value of the extraction flag SelectFlag(k) to 1 for a sample of an even-numbered index even when the sample is not near a sample having a maximum amplitude value, as expressed by equation 12. Accordingly, even when a sample having a large amplitude is present in a band far from a sample having a maximum amplitude value, this sample or a sample having an amplitude near the sample this sample can be extracted. Sample group extracting section382outputs the estimated spectrum S3′(k), and the maximum amplitude value MaxValuepand the extraction flag SelectFlag(k) for each sub-band to logarithmic gain calculating section383.

Processes performed by maximum amplitude value search section381and sample group extracting section382are similar to processes performed by maximum amplitude value search section253and sample group extracting section282of encoding apparatus101.

Logarithmic gain applying section383calculates Signp(k) that indicates a sign (−, −) of an extracted sample group, from the estimated spectrum S3′(k) and the extraction flag SelectFlag(k) that are input from sample group extracting section382, as expressed by equation 18. That is, as expressed by equation 18, logarithmic gain applying section383calculates Signp(k)=1 when the sign of the extracted sample is “+” (when S3′(k)≧0), and calculates Signp(k)=−1 in other cases (when the sign of the extracted sample is “−” (when Signp(k)≧0).

Logarithmic gain applying section383calculates a decoded spectrum S5′(k), following equations 19 and 20, for a sample where the value of the extraction flag SelectFlag(k) is 1, based on the estimated spectrum S3′(k), the maximum amplitude value MaxValuep, and the extraction flag SelectFlag(k) that are input from sample group extracting section382, and based on the quantized logarithmic gain α2Qpthat is input from gain decoding section354, and the sign Signp(k) that is calculated following equation 18.

That is, logarithmic gain applying section383applies the logarithmic gain α2pto only a sample that is partially selected by sample extracting section382(a sample of the extraction flag SelectFlag(k=1). Logarithmic gain applying section383outputs the decoded spectrum S5′(k) to orthogonal transform processing section356. In this case, a low frequency part (0≦k<FL) of the decoded spectrum S5′(k) is comprised of the first layer decoded spectrum S1(k), and a high frequency part (FL≦k<FH) of the decoded spectrum S5′(k) is comprised of the spectrum obtained by performing energy adjustment in the logarithmic domain to the estimated spectrum S3′(k). However, for a sample that is not selected by sample extracting section382(a sample of the extraction flag SelectFlag(k)=0), in the high frequency part (FL≦k<FH) of the decoded spectrum S5′(k), a value of this sample is set as the value of the estimated spectrum S3′(k).

The process of spectrum adjusting section396is explained above.

The process of decoding apparatus113according to the present embodiment is as explained above.

As explained above, according to the present embodiment, in the encoding/decoding for estimating a spectrum of a high frequency part by performing a band expansion by using a spectrum of a low frequency part, the spectrum of the high frequency part is estimated by using a decoded low frequency spectrum, and thereafter, a sample is selected (thinned) in each sub-band of the estimated spectrum, and a gain adjustment in the logarithmic domain is performed for only the selected sample. Unlike in Embodiment 1, the encoding apparatus and the decoding apparatus calculate a gain adjustment parameter (a logarithmic gain) without taking into account a distance from a maximum amplitude value, and the decoding apparatus takes into account a distance from a maximum amplitude value within the sub-band only when a gain adjustment parameter (a logarithmic gain) is applied. Based on this configuration, the volume of arithmetic operations can be reduced more than that in Embodiment 1.

As explained in the present embodiment, it is confirmed by experiments that there is no degradation of sound quality, even when the encoding apparatus calculates a gain adjustment parameter from only a sample of an even index, and when the decoding apparatus takes into account a distance from a sample having a maximum amplitude value within a sub-band and applies a gain adjustment parameter to an extracted sample. That is, it can be said that there is no problem even when a sample group to be used for calculating a gain adjustment parameter does not necessary match a sample group to be used for applying the gain adjustment parameter. This indicates, as explained in the present embodiment, for example, that the encoding apparatus and the decoding apparatus can efficiently calculate a gain adjustment parameter even when all samples are not extracted, by uniformly extracting samples in whole sub-bands. This also indicates that the decoding apparatus can efficiently reduce the volume of arithmetic operations by applying the obtained gain adjustment parameter to only samples extracted by taking into account a distance from a sample having a maximum amplitude value within a sub-band. According to the present embodiment, the volume of arithmetic operations is more reduced than that in Embodiment 1, without degrading sound quality, by employing this configuration.

In the present embodiment, it is explained as an example that the encoding/decoding process of a low frequency component of an input signal and the encoding/decoding process of a high frequency component of an input signal are performed separately, that is, the encoding/decoding process is performed in a layered structure of two layers. However, application of the present invention is not limited to this, and the invention can be also similarly applied to the case of performing the encoding/decoding in a layered structure of three or more layers. When a layered encoding section of three or more layers is considered, in a second layer decoding section that generates a local decoded signal of a second layer decoding section, a sample group to which a gain adjustment parameter (a logarithmic gain) is applied can be a sample group which does not take into account a distance from a sample having a maximum amplitude value which is calculated within the encoding apparatus according to the present embodiment, or can be a sample group which takes into account a distance from a sample having a maximum amplitude value which is calculated within the decoding apparatus according to the present embodiment.

In the present embodiment, in the setting of an extraction flag, a value of the extraction flag is set to 1 only when an index of a sample is an even number. However, application of the present invention is not limited to this, and the invention can be also similarly applied to the case where a surplus to the index 3 is 0, for example.

Each embodiment of the present invention is explained above.

In the above embodiments, it is explained as an example that a number J of sub-bands obtained by dividing the high frequency part of the input spectrum S2(k) in gain encoding section265(or gain encoding section235) is different from a number F of sub-bands obtained by dividing the high frequency part of the input spectrum S2(k) in search section263. However, setting is not limited to this method in the present invention, and a number of sub-bands obtained by dividing the high frequency part of the input spectrum S2(k) in gain encoding section265(or gain encoding section235) can be set to P.

In the above embodiments, a configuration is explained that estimates a high frequency part of the input spectrum by using a low frequency part of the first layer decoded spectrum obtained from the first layer decoding section. However, a configuration is not limited to this in the present invention, and the invention can be also similarly applied to a configuration that estimates a high frequency part of the input spectrum by using a low frequency part of the input spectrum instead of the first layer decoded spectrum. In this configuration, the encoding apparatus calculates encoded information (the second layer encoded information) for generating a high frequency component of the input spectrum from a low frequency component of the input spectrum, and the decoding apparatus applies this encoded information to the first layer decoded spectrum, and generates a high frequency component of a decoded spectrum.

In the above embodiments, a process is explained as an example that reduces the volume of arithmetic operations and improves sound quality in the configuration that calculates and applies a parameter for adjusting an energy ratio in a logarithmic domain based on the process in Patent Literature 1. However, application of the present invention is not limited to this, and the invention can be similarly applied to a configuration that adjusts an energy ratio in a nonlinear domain transform other than a logarithmic transform. The invention can be also applied to a linear domain transform as well as a nonlinear domain transform.

In the above embodiments, a process is explained as an example that reduces the volume of arithmetic operations and improves sound quality in the configuration that calculates and applies a parameter for adjusting an energy ratio in a logarithmic domain in a band expansion process based on the process in Patent Literature 1. However, application of the present invention is not limited to this, and the invention can be also similarly applied to a process other than the band expansion process.

The encoding apparatus, the decoding apparatus, and the method therefor are not limited to the above embodiments, and various modifications can be also implemented. For example, these embodiments can be suitably combined for implementation.

In the above embodiments, it is explained as an example that the decoding apparatus performs a process by using encoded information transmitted from the encoding apparatus in each embodiment. However, the process is not limited to the above in the present invention, and the decoding apparatus can also perform the process by using encoded information that contains necessary parameters and data, by not necessarily using encoded information from the encoding apparatus in the above embodiments.

In the above embodiments, although a speech signal is explained to be encoded, a music signal can be also encoded, and an acoustic signal that contains both of these signals can be also encoded.

The present invention can be also applied to the case of recording and writing a signal processing program into a mechanically readable recording medium such as a memory, a disk, a tape, a CD, and a DVD, and performing operation, and can also obtain operation and effects similar to those in the present embodiments.

Also, although cases have been described with the above embodiment as examples where the present invention is configured by hardware, the present invention can also be realized by software.

Each function block employed in the description of each of the aforementioned embodiments may typically be implemented as an LSI constituted by an integrated circuit. These may be individual chips or partially or totally contained on a single chip. “LSI” is adopted here but this may also be referred to as “IC,” “system LSI,” “super LSI,” or “ultra LSI” depending on differing extents of integration.

Further, the method of circuit integration is not limited to LSI's, and implementation using dedicated circuitry or general purpose processors is also possible. After LSI manufacture, utilization of a programmable FPGA (Field Programmable Gate Array) or a reconfigurable processor where connections and settings of circuit cells within an LSI can be reconfigured is also possible.

The disclosures of Japanese Patent Application No. 2009-044676, filed on Feb. 26, 2009, Japanese Patent Application No. 2009-089656, filed on Apr. 2, 2009, and Japanese Patent Application No. 2010-001654, filed on Jan. 7, 2010, including the specifications, drawings, and abstracts, are incorporated herein by reference in their entirety.

INDUSTRIAL APPLICABILITY

The encoding apparatus, the decoding apparatus, and the method therefor according to the present invention can improve quality of a decoded signal when estimating a spectrum of a high frequency part by performing a band expansion by using a spectrum of a low frequency part, and can be applied to a packet communication system, and a mobile communication system, for example.

REFERENCE SIGNS LIST