Added functions for computing the convolution and cross-correlation between

two matrices.

dlib/matrix.h

@@ -10,6 +10,7 @@
 #include "matrix/matrix_assign.h"
 #include "matrix/matrix_la.h"
 #include "matrix/symmetric_matrix_cache.h"
+#include "matrix/matrix_conv.h"
 
 #ifdef DLIB_USE_BLAS
 #include "matrix/matrix_blas_bindings.h"

dlib/matrix/matrix_conv_abstract.h

+// Copyright (C) 2011  Davis E. King (davis@dlib.net)
+// License: Boost Software License   See LICENSE.txt for the full license.
+#undef DLIB_MATRIx_CONV_ABSTRACT_H__
+#ifdef DLIB_MATRIx_CONV_ABSTRACT_H__
+
+#include "matrix_abstract.h"
+
+namespace dlib
+{
+
+// ----------------------------------------------------------------------------------------
+
+    const matrix_exp conv (
+        const matrix_exp& m1,
+        const matrix_exp& m2
+    );
+    /*!
+        requires
+            - m1 and m2 both contain elements of the same type
+        ensures
+            - returns a matrix R such that:
+                - R is the convolution of m1 with m2.  In particular, this function is 
+                  equivalent to performing the following in matlab: R = conv2(m1,m2).
+                - R::type == the same type that was in m1 and m2.
+                - R.nr() == m1.nr()+m2.nr()-1
+                - R.nc() == m1.nc()+m2.nc()-1
+    !*/
+
+// ----------------------------------------------------------------------------------------
+
+    const matrix_exp xcorr (
+        const matrix_exp& m1,
+        const matrix_exp& m2
+    );
+    /*!
+        requires
+            - m1 and m2 both contain elements of the same type
+        ensures
+            - returns a matrix R such that:
+                - R is the cross-correlation of m1 with m2.  In particular, this
+                  function returns conv(m1,flip(m2)).
+                - R::type == the same type that was in m1 and m2.
+                - R.nr() == m1.nr()+m2.nr()-1
+                - R.nc() == m1.nc()+m2.nc()-1
+    !*/
+
+// ----------------------------------------------------------------------------------------
+
+    const matrix_exp conv_same (
+        const matrix_exp& m1,
+        const matrix_exp& m2
+    );
+    /*!
+        requires
+            - m1 and m2 both contain elements of the same type
+        ensures
+            - returns a matrix R such that:
+                - R is the convolution of m1 with m2.  In particular, this function is 
+                  equivalent to performing the following in matlab: R = conv2(m1,m2,'same').
+                  In particular, this means the result will have the same dimensions as m1 and will
+                  contain the central part of the full convolution.  This means conv_same(m1,m2) is 
+                  equivalent to subm(conv(m1,m2), m2.nr()/2, m2.nc()/2, m1.nr(), m1.nc()).
+                - R::type == the same type that was in m1 and m2.
+                - R.nr() == m1.nr()
+                - R.nc() == m1.nc()
+    !*/
+
+// ----------------------------------------------------------------------------------------
+
+    const matrix_exp xcorr_same (
+        const matrix_exp& m1,
+        const matrix_exp& m2
+    );
+    /*!
+        requires
+            - m1 and m2 both contain elements of the same type
+        ensures
+            - returns a matrix R such that:
+                - R is the cross-correlation of m1 with m2.  In particular, this
+                  function returns conv_same(m1,flip(m2)).
+                - R::type == the same type that was in m1 and m2.
+                - R.nr() == m1.nr()
+                - R.nc() == m1.nc()
+    !*/
+
+// ----------------------------------------------------------------------------------------
+
+    const matrix_exp conv_valid (
+        const matrix_exp& m1,
+        const matrix_exp& m2
+    );
+    /*!
+        requires
+            - m1 and m2 both contain elements of the same type
+        ensures
+            - returns a matrix R such that:
+                - R is the convolution of m1 with m2.  In particular, this function is 
+                  equivalent to performing the following in matlab: R = conv2(m1,m2,'valid').
+                  In particular, this means only elements of the convolution which don't require 
+                  zero padding are included in the result.
+                - R::type == the same type that was in m1 and m2.
+                - if (m1 has larger dimensions than m2) then
+                    - R.nr() == m1.nr()-m2.nr()+1
+                    - R.nc() == m1.nc()-m2.nc()+1
+                - else
+                    - R.nr() == 0
+                    - R.nc() == 0
+    !*/
+
+// ----------------------------------------------------------------------------------------
+
+    const matrix_exp xcorr_valid (
+        const matrix_exp& m1,
+        const matrix_exp& m2
+    );
+    /*!
+        requires
+            - m1 and m2 both contain elements of the same type
+        ensures
+            - returns a matrix R such that:
+                - R is the cross-correlation of m1 with m2.  In particular, this
+                  function returns conv_valid(m1,flip(m2)).
+                - R::type == the same type that was in m1 and m2.
+                - if (m1 has larger dimensions than m2) then
+                    - R.nr() == m1.nr()-m2.nr()+1
+                    - R.nc() == m1.nc()-m2.nc()+1
+                - else
+                    - R.nr() == 0
+                    - R.nc() == 0
+    !*/
+
+// ----------------------------------------------------------------------------------------
+
+}
+
+#endif // DLIB_MATRIx_CONV_ABSTRACT_H__
+
+