matlab中的conv2卷积运算的三种形式

thinkfunny

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matlab中的conv2是用于对二维数据进行卷积运算，有三个参数可供选择，下面是help content of conv2

conv2 Two dimensional convolution.

& s2 F2 K- F1 Z- V5 N    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]).
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    C = conv2(H1, H2, A) first convolves each column of A with the vector
2 z2 _0 Z6 j& b6 Z( ^8 M7 c    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
* h- P) D# S& |8 p    round-off.
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; U% N# i2 z! P) E  k6 n  ^    C = conv2(..., SHAPE) returns a subsection of the 2-D
: F5 x/ \, b8 S' X. x3 x+ s4 y    convolution with size specified by SHAPE:
" y  [# J% a4 }% b% ^  t) c2 @      'full'  - (default) returns the full 2-D convolution,
      'same'  - returns the central part of the convolution
                that is the same size as A.
2 q8 d' g; f- j1 G: |, B! ?/ u      'valid' - returns only those parts of the convolution
1 O, Y  m+ \$ \* S                that are computed without the zero-padded edges.
                size(C) = max([ma-max(0,mb-1),na-max(0,nb-1)],0).


: t3 I& n$ h. f& o* n6 T8 b. m$ I3 E$ Y关于full, same以及valid三种参数的区别，如下面的实例所示：

! S( j% O* ^$ b- i; Qfull
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1 q) u1 f6 f) {7 nsame
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9 L- C) O1 j; b/ G1 e! k5 c; \valid
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yin123

三种形式的matlab中的conv2卷积运算