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Documentation> MATLAB API> MISC - vl_alldist2

D = VL_ALLDIST2(X,Y) returns the pairwise distance matrix D of the columns of S1 and S2, yielding

      D(i,j) = sum (X(:,i) - Y(:,j)).^2

VL_ALLDIST2(X) returns the pairwise distance matrix fo the columns of S, yielding

      D(i,j) = sum (X(:,i) - X(:,j)).^2

VL_ALLDIST2(...,'METRIC') changes the computed distance. Supported values for METRIC are

     METRIC  D(i,j)
     --------------------------------------------------------
      LINF   max |X  - Y|
      L2     sum (X  - Y).^2
      L1     sum |X  - Y|
      L0     sum (X ~= Y)
      CHI2   sum (X  - Y).^2 ./ (X + Y)
      HELL   sum (X^.5 - Y^.5) .^ 2

(Notice that the standard definition of chi2 is half of what is computed here).

VL_ALLDIST2(...,'KERNEL') computes the following 'kernels' K:

     KERNEL  K(i,j)
     ---------------------------------------------------------
      KL2    sum X .* Y
      KL1    sum min (X, Y)
      KCHI2  2 * sum (X .* Y) ./ (X + Y)
      KHELL  (X .* Y) .^ 0.5

The constant are chosen so that D(i,j) = K(i,i) + K(j,j) - 2 K(i,j) where D is the metric corresponding to the kenrel (if the arguments are non-negative vectors). Each kernel can be interpreted as the inner product inducing the corresponding metric in an embedding of the real space into an approrpiate reproducing Kenrel Hilbert space.

VL_ALLDIST2() supports several storage classes. X and Y must have the same storage class. The sotrage class of D is promoted to reduce the chance of overvlow, but this is not checked.

      X & Y class      D class
     ---------------------------
      UINT8            UINT32
       INT8             INT32
      UINT16           UINT32
       INT16            INT32
      UINT32           UINT32
       INT32            INT32
      SINGLE           SINGLE
      DOUBLE           DOUBLE

Warning: Both chi2 and kchi2 use integer math when presented with integer data types. This can easily result in zeros where you did not expect them.

See also: VL_HELP().