tns.c

dsp上用c语言实现的aac音频算法的编解码器代码

        numberOfWindows = 1;
        windowSize = BLOCK_LEN_LONG;
        startBand = tnsInfo->tnsMinBandNumberLong;
        stopBand = numberOfBands;
        startBand = min(startBand,tnsInfo->tnsMaxBandsLong);
        stopBand = min(stopBand,tnsInfo->tnsMaxBandsLong);
        break;
    }

    /* Make sure that start and stop bands < maxSfb */
    /* Make sure that start and stop bands >= 0 */
    startBand = min(startBand,maxSfb);
    stopBand = min(stopBand,maxSfb);
    startBand = max(startBand,0);
    stopBand = max(stopBand,0);


    /* Perform filtering for each window */
    for(w=0;w<numberOfWindows;w++)
    {
        TnsWindowData* windowData = &tnsInfo->windowData[w];
        TnsFilterData* tnsFilter = windowData->tnsFilter;

        startIndex = w * windowSize + sfbOffsetTable[startBand];
        length = sfbOffsetTable[stopBand] - sfbOffsetTable[startBand];

        if (tnsInfo->tnsDataPresent  &&  windowData->numFilters) {  /* Use TNS */
            TnsFilter(length,&spec[startIndex],tnsFilter);
        }
    }
}


/*****************************************************/
/* TnsFilter:                                        */
/*   Filter the given spec with specified length     */
/*   using the coefficients specified in filter.     */
/*   Not that the order and direction are specified  */
/*   withing the TNS_FILTER_DATA structure.          */
/*****************************************************/
static void TnsFilter(int length,double* spec,TnsFilterData* filter)
{
    int i,j,k=0;
    int order=filter->order;
    double* a=filter->aCoeffs;

    /* Determine loop parameters for given direction */
    if (filter->direction) {

        /* Startup, initial state is zero */
        for (i=length-2;i>(length-1-order);i--) {
            k++;
            for (j=1;j<=k;j++) {
                spec[i]-=spec[i+j]*a[j];
            }
        }

        /* Now filter completely inplace */
        for (i=length-1-order;i>=0;i--) {
            for (j=1;j<=order;j++) {
                spec[i]-=spec[i+j]*a[j];
            }
        }


    } else {

        /* Startup, initial state is zero */
        for (i=1;i<order;i++) {
            for (j=1;j<=i;j++) {
                spec[i]-=spec[i-j]*a[j];
            }
        }

        /* Now filter completely inplace */
        for (i=order;i<length;i++) {
            for (j=1;j<=order;j++) {
                spec[i]-=spec[i-j]*a[j];
            }
        }
    }
}


/********************************************************/
/* TnsInvFilter:                                        */
/*   Inverse filter the given spec with specified       */
/*   length using the coefficients specified in filter. */
/*   Not that the order and direction are specified     */
/*   withing the TNS_FILTER_DATA structure.             */
/********************************************************/
static void TnsInvFilter(int length,double* spec,TnsFilterData* filter)
{
    int i,j,k=0;
    int order=filter->order;
    double* a=filter->aCoeffs;
    double* temp;

    temp = (double *)AllocMemory(length * sizeof (double));

    /* Determine loop parameters for given direction */
    if (filter->direction) {

        /* Startup, initial state is zero */
        temp[length-1]=spec[length-1];
        for (i=length-2;i>(length-1-order);i--) {
            temp[i]=spec[i];
            k++;
            for (j=1;j<=k;j++) {
                spec[i]+=temp[i+j]*a[j];
            }
        }

        /* Now filter the rest */
        for (i=length-1-order;i>=0;i--) {
            temp[i]=spec[i];
            for (j=1;j<=order;j++) {
                spec[i]+=temp[i+j]*a[j];
            }
        }


    } else {

        /* Startup, initial state is zero */
        temp[0]=spec[0];
        for (i=1;i<order;i++) {
            temp[i]=spec[i];
            for (j=1;j<=i;j++) {
                spec[i]+=temp[i-j]*a[j];
            }
        }

        /* Now filter the rest */
        for (i=order;i<length;i++) {
            temp[i]=spec[i];
            for (j=1;j<=order;j++) {
                spec[i]+=temp[i-j]*a[j];
            }
        }
    }
    if (temp) FreeMemory(temp);
}





/*****************************************************/
/* TruncateCoeffs:                                   */
/*   Truncate the given reflection coeffs by zeroing */
/*   coefficients in the tail with absolute value    */
/*   less than the specified threshold.  Return the  */
/*   truncated filter order.                         */
/*****************************************************/
static int TruncateCoeffs(int fOrder,double threshold,double* kArray)
{
    int i;

    for (i = fOrder; i >= 0; i--) {
        kArray[i] = (fabs(kArray[i])>threshold) ? kArray[i] : 0.0;
        if (kArray[i]!=0.0) return i;
    }

    return 0;
}

/*****************************************************/
/* QuantizeReflectionCoeffs:                         */
/*   Quantize the given array of reflection coeffs   */
/*   to the specified resolution in bits.            */
/*****************************************************/
static void QuantizeReflectionCoeffs(int fOrder,
                              int coeffRes,
                              double* kArray,
                              int* indexArray)
{
    double iqfac,iqfac_m;
    int i;

    iqfac = ((1<<(coeffRes-1))-0.5)/(M_PI/2);
    iqfac_m = ((1<<(coeffRes-1))+0.5)/(M_PI/2);

    /* Quantize and inverse quantize */
    for (i=1;i<=fOrder;i++) {
        indexArray[i] = (int)(0.5+(asin(kArray[i])*((kArray[i]>=0)?iqfac:iqfac_m)));
        kArray[i] = sin((double)indexArray[i]/((indexArray[i]>=0)?iqfac:iqfac_m));
    }
}

/*****************************************************/
/* Autocorrelation,                                  */
/*   Compute the autocorrelation function            */
/*   estimate for the given data.                    */
/*****************************************************/
static void Autocorrelation(int maxOrder,        /* Maximum autocorr order */
                     int dataSize,        /* Size of the data array */
                     double* data,        /* Data array */
                     double* rArray)      /* Autocorrelation array */
{
    int order,index;

    for (order=0;order<=maxOrder;order++) {
        rArray[order]=0.0;
        for (index=0;index<dataSize;index++) {
            rArray[order]+=data[index]*data[index+order];
        }
        dataSize--;
    }
}



/*****************************************************/
/* LevinsonDurbin:                                   */
/*   Compute the reflection coefficients for the     */
/*   given data using LevinsonDurbin recursion.      */
/*   Return the prediction gain.                     */
/*****************************************************/
static double LevinsonDurbin(int fOrder,          /* Filter order */
                      int dataSize,        /* Size of the data array */
                      double* data,        /* Data array */
                      double* kArray)      /* Reflection coeff array */
{
    int order,i;
    double signal;
    double error, kTemp;                /* Prediction error */
    double aArray1[TNS_MAX_ORDER+1];    /* Predictor coeff array */
    double aArray2[TNS_MAX_ORDER+1];    /* Predictor coeff array 2 */
    double rArray[TNS_MAX_ORDER+1];     /* Autocorrelation coeffs */
    double* aPtr = aArray1;             /* Ptr to aArray1 */
    double* aLastPtr = aArray2;         /* Ptr to aArray2 */
    double* aTemp;

    /* Compute autocorrelation coefficients */
    Autocorrelation(fOrder,dataSize,data,rArray);
    signal=rArray[0];   /* signal energy */

    /* Set up pointers to current and last iteration */
    /* predictor coefficients.                       */
    aPtr = aArray1;
    aLastPtr = aArray2;
    /* If there is no signal energy, return */
    if (!signal) {
        kArray[0]=1.0;
        for (order=1;order<=fOrder;order++) {
            kArray[order]=0.0;
        }
        return 0;

    } else {

        /* Set up first iteration */
        kArray[0]=1.0;
        aPtr[0]=1.0;        /* Ptr to predictor coeffs, current iteration*/
        aLastPtr[0]=1.0;    /* Ptr to predictor coeffs, last iteration */
        error=rArray[0];

        /* Now perform recursion */
        for (order=1;order<=fOrder;order++) {
            kTemp = aLastPtr[0]*rArray[order-0];
            for (i=1;i<order;i++) {
                kTemp += aLastPtr[i]*rArray[order-i];
            }
            kTemp = -kTemp/error;
            kArray[order]=kTemp;
            aPtr[order]=kTemp;
            for (i=1;i<order;i++) {
                aPtr[i] = aLastPtr[i] + kTemp*aLastPtr[order-i];
            }
            error = error * (1 - kTemp*kTemp);

            /* Now make current iteration the last one */
            aTemp=aLastPtr;
            aLastPtr=aPtr;      /* Current becomes last */
            aPtr=aTemp;         /* Last becomes current */
        }
        return signal/error;    /* return the gain */
    }
}


/*****************************************************/
/* StepUp:                                           */
/*   Convert reflection coefficients into            */
/*   predictor coefficients.                         */
/*****************************************************/
static void StepUp(int fOrder,double* kArray,double* aArray)
{
    double aTemp[TNS_MAX_ORDER+2];
    int i,order;

    aArray[0]=1.0;
    aTemp[0]=1.0;
    for (order=1;order<=fOrder;order++) {
        aArray[order]=0.0;
        for (i=1;i<=order;i++) {
            aTemp[i] = aArray[i] + kArray[order]*aArray[order-i];
        }
        for (i=1;i<=order;i++) {
            aArray[i]=aTemp[i];
        }
    }
}