The conv2 in matlab is used to perform convolution operations on two-dimensional data. There are three parameters to choose from. The following is the help content of conv2
conv2 Two dimensional convolution.
C = conv2(A, B) performs the 2-D convolution of matrices A and B.If [ma,na] = size(A), [mb,nb] = size(B), and [mc,nc] = size(C), then
mc = max([ma+mb-1,ma,mb]) and nc = max([na+nb-1,na,nb]).
C = conv2(H1, H2, A) first convolves each column of A with the vector
H1 and then convolves each row of the result with the vector H2. If
n1 = length(H1), n2 = length(H2), and [mc,nc] = size(C) then
mc = max([ma+n1-1,ma,n1]) and nc = max([na+n2-1,na,n2]).
conv2(H1, H2, A) is equivalent to conv2(H1(:)*H2(:).', A) up to
round-off.
C = conv2(..., SHAPE) returns a subsection of the 2-D
convolution with size specified by SHAPE:
'full' - (default) returns the full 2-D convolution,
'same' - returns the central part of the convolution
that is the same size as A.
'valid' - returns only those parts of the convolution
that are computed without the zero-padded edges.
size(C) = max([ma-max(0,mb-1),na-max(0,nb-1)],0).
The difference between full, same and valid parameters is shown in the following example:
full
same
valid
The conv2 in matlab is used to perform convolution operations on two-dimensional data. There are three parameters to choose from. The following is the help content of conv2
conv2 Two dimensional convolution.
C = conv2(A, B) performs the 2-D convolution of matrices A and B.If [ma,na] = size(A), [mb,nb] = size(B), and [mc,nc] = size(C), then
mc = max([ma+mb-1,ma,mb]) and nc = max([na+nb-1,na,nb]).
C = conv2(H1, H2, A) first convolves each column of A with the vector
H1 and then convolves each row of the result with the vector H2. If
n1 = length(H1), n2 = length(H2), and [mc,nc] = size(C) then
mc = max([ma+n1-1,ma,n1]) and nc = max([na+n2-1,na,n2]).
conv2(H1, H2, A) is equivalent to conv2(H1(:)*H2(:).', A) up to
round-off.
C = conv2(..., SHAPE) returns a subsection of the 2-D
convolution with size specified by SHAPE:
'full' - (default) returns the full 2-D convolution,
'same' - returns the central part of the convolution
that is the same size as A.
'valid' - returns only those parts of the convolution
that are computed without the zero-padded edges.
size(C) = max([ma-max(0,mb-1),na-max(0,nb-1)],0).
The difference between full, same and valid parameters is shown in the following example:
full
same
valid