[Vapor-cvs] vapor/include/vapor Lifting1D.h,1.6,1.7

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Update of /cvsroot/vapor/vapor/include/vapor
In directory sc8-pr-cvs9.sourceforge.net:/tmp/cvs-serv24419

Modified Files:
	Lifting1D.h 
Log Message:
Added 'stride' parameter to permit multi-dimensional transforms without transposing the array

Index: Lifting1D.h
===================================================================
RCS file: /cvsroot/vapor/vapor/include/vapor/Lifting1D.h,v
retrieving revision 1.6
retrieving revision 1.7
diff -C2 -d -r1.6 -r1.7
*** Lifting1D.h	13 Jul 2006 23:10:41 -0000	1.6
--- Lifting1D.h	31 Aug 2006 22:19:16 -0000	1.7
***************
*** 51,55 ****
   //! \sa InverseTransform(), Lifting1D()
   //
!  void	ForwardTransform(Data_T *data);

   //! Apply inverse lifting transform
--- 51,55 ----
   //! \sa InverseTransform(), Lifting1D()
   //
!  void	ForwardTransform(Data_T *data, int stride = 1);

   //! Apply inverse lifting transform
***************
*** 60,64 ****
   //! \sa ForwardTransform(), Lifting1D()
   //
!  void	InverseTransform(Data_T *data);

  private:
--- 60,64 ----
   //! \sa ForwardTransform(), Lifting1D()
   //
!  void	InverseTransform(Data_T *data, int stride = 1);

  private:
***************
*** 114,123 ****
   );

!  void FLWT1D_Predict(Data_T*, const long, const long, double *);
!  void FLWT1D_Update(Data_T *, const long, const long, const double*);

!  void forward_transform1d_haar(Data_T *data, int width);

!  void inverse_transform1d_haar(Data_T *data, int width);

--- 114,123 ----
   );

!  void FLWT1D_Predict(Data_T*, const long, const long, double *, int stride);
!  void FLWT1D_Update(Data_T *, const long, const long, const double*, int stride);

!  void forward_transform1d_haar(Data_T *data, int width, int stride);

!  void inverse_transform1d_haar(Data_T *data, int width, int stride);

***************
*** 312,323 ****
  //
  template <class Data_T> void   Lifting1D<Data_T>::ForwardTransform(
! 	Data_T *data
  ) {
  	if (n_c == 1 && ntilde_c == 1) {
! 		forward_transform1d_haar(data, width_c);
  	}
  	else {
! 		FLWT1D_Predict (data, width_c, n_c, fwd_filter_c);
! 		FLWT1D_Update (data, width_c, ntilde_c, fwd_lifting_c);
  	}

--- 312,323 ----
  //
  template <class Data_T> void   Lifting1D<Data_T>::ForwardTransform(
! 	Data_T *data, int stride
  ) {
  	if (n_c == 1 && ntilde_c == 1) {
! 		forward_transform1d_haar(data, width_c, stride);
  	}
  	else {
! 		FLWT1D_Predict (data, width_c, n_c, fwd_filter_c, stride);
! 		FLWT1D_Update (data, width_c, ntilde_c, fwd_lifting_c, stride);
  	}

***************
*** 325,329 ****
  		// normalize the detail coefficents
  		for(unsigned int i=1; i<width_c; i+=2) {
! 			data[i] /= _nfactor;
  		}
  	}
--- 325,329 ----
  		// normalize the detail coefficents
  		for(unsigned int i=1; i<width_c; i+=2) {
! 			data[i*stride] /= _nfactor;
  		}
  	}
***************
*** 339,357 ****
  //
  template <class Data_T> void Lifting1D<Data_T>::InverseTransform(
! 	Data_T *data
  ) {
  	if (_nfactor != 1.0) {
  		// un-normalize the detail coefficents
  		for(unsigned int i=1; i<width_c; i+=2) {
! 			data[i] *= _nfactor;
  		}
  	}

  	if (n_c == 1 && ntilde_c == 1) {
! 		inverse_transform1d_haar(data, width_c);
  	}
  	else {
! 		FLWT1D_Update (data, width_c, ntilde_c, inv_lifting_c);
! 		FLWT1D_Predict (data, width_c, n_c, inv_filter_c);
  	}
  }
--- 339,357 ----
  //
  template <class Data_T> void Lifting1D<Data_T>::InverseTransform(
! 	Data_T *data, int stride
  ) {
  	if (_nfactor != 1.0) {
  		// un-normalize the detail coefficents
  		for(unsigned int i=1; i<width_c; i+=2) {
! 			data[i*stride] *= _nfactor;
  		}
  	}

  	if (n_c == 1 && ntilde_c == 1) {
! 		inverse_transform1d_haar(data, width_c, stride);
  	}
  	else {
! 		FLWT1D_Update (data, width_c, ntilde_c, inv_lifting_c, stride);
! 		FLWT1D_Predict (data, width_c, n_c, inv_filter_c, stride);
  	}
  }
***************
*** 995,999 ****
  	const long width,
  	const long N,
! 	double *filter
  ) {
      register Data_T *lambdaPtr,	//pointer to Lambda coeffs
--- 995,1000 ----
  	const long width,
  	const long N,
! 	double *filter, 
! 	int stride
  ) {
      register Data_T *lambdaPtr,	//pointer to Lambda coeffs
***************
*** 1013,1017 ****
      /************************************************/
      len       = CEIL(width, 1);   /* number of coefficients at current level */
!     stepIncr  = 1 << 1;   /* step size betweeen coefficients */

      /************************************************/
--- 1014,1018 ----
      /************************************************/
      len       = CEIL(width, 1);   /* number of coefficients at current level */
!     stepIncr  = stride << 1;   /* step size betweeen coefficients */

      /************************************************/
***************
*** 1086,1090 ****
  	const long width,
  	const long nTilde,
! 	const double * lc
  ) {
      const register double * lcPtr;   /* pointer to lifting coefficient values */
--- 1087,1092 ----
  	const long width,
  	const long nTilde,
! 	const double *lc,
! 	int stride
  ) {
      const register double * lcPtr;   /* pointer to lifting coefficient values */
***************
*** 1106,1110 ****
      /************************************************/
      len      = CEIL(width, 1);   /* number of coefficients at current level */
!     stepIncr = 1 << 1;   /* step size between coefficients */
      noGammas = len >> 1 ;          /* number of Gamma coefficients */

--- 1108,1112 ----
      /************************************************/
      len      = CEIL(width, 1);   /* number of coefficients at current level */
!     stepIncr = stride << 1;   /* step size between coefficients */
      noGammas = len >> 1 ;          /* number of Gamma coefficients */

***************
*** 1168,1172 ****
  template <class Data_T> void Lifting1D<Data_T>::forward_transform1d_haar(
  	Data_T *data,
! 	int width
  ) {
  	int	i;
--- 1170,1175 ----
  template <class Data_T> void Lifting1D<Data_T>::forward_transform1d_haar(
  	Data_T *data,
! 	int width,
! 	int stride
  ) {
  	int	i;
***************
*** 1176,1179 ****
--- 1179,1184 ----
  	double	lsum = 0.0;	// sum of lambda values
  	double	lave = 0.0;	// average of lambda values
+ 	int stepIncr = stride << 1;   // step size betweeen coefficients
+ 

      nG = (width >> 1);
***************
*** 1187,1191 ****

  		for(i=0;i<width;i++) {
! 			t += data[i];
  		}
  		lave = t / (double) width;
--- 1192,1196 ----

  		for(i=0;i<width;i++) {
! 			t += data[i*stride];
  		}
  		lave = t / (double) width;
***************
*** 1193,1201 ****

  	for (i=0; i<nG; i++) {
! 		data[1] = data[1] - data[0];	// gamma
! 		data[0] = (Data_T)(data[0] + (data[1] /2.0)); // lambda
  		lsum += data[0];

! 		data += 2;
  	}

--- 1198,1206 ----

  	for (i=0; i<nG; i++) {
! 		data[stride] = data[stride] - data[0];	// gamma
! 		data[0] = (Data_T)(data[0] + (data[stride] /2.0)); // lambda
  		lsum += data[0];

! 		data += stepIncr;
  	}

***************
*** 1213,1217 ****
  template <class Data_T> void Lifting1D<Data_T>::inverse_transform1d_haar(
  	Data_T *data,
! 	int width
  ) {
  	int	i,j;
--- 1218,1223 ----
  template <class Data_T> void Lifting1D<Data_T>::inverse_transform1d_haar(
  	Data_T *data,
! 	int width,
! 	int stride
  ) {
  	int	i,j;
***************
*** 1221,1224 ****
--- 1227,1232 ----
  	double	lave = 0.0;	// average of lambda values

+ 	int stepIncr = stride << 1;   // step size betweeen coefficients
+ 
  	nG = (width >> 1);
  	nL = width - nG;
***************
*** 1230,1234 ****
          double  t = 0.0;

! 		for(i=0,j=0;i<nL;i++,j+=2) {
              t += data[j];
          }
--- 1238,1242 ----
          double  t = 0.0;

! 		for(i=0,j=0;i<nL;i++,j+=stepIncr) {
              t += data[j];
          }
***************
*** 1237,1245 ****

  	for (i=0; i<nG; i++) {
! 		data[0] = (Data_T)(data[0] - (data[1] * 0.5));
! 		data[1] = data[1] + data[0];
! 		lsum += data[0] +  data[1];

! 		data += 2;
  	}

--- 1245,1253 ----

  	for (i=0; i<nG; i++) {
! 		data[0] = (Data_T)(data[0] - (data[stride] * 0.5));
! 		data[stride] = data[stride] + data[0];
! 		lsum += data[0] +  data[stride];

! 		data += stepIncr;
  	}