NC = wthcoef2('type',C,S,N,T,SORH)
returns the horizontal, vertical, or diagonal coefficients obtained from the wavelet
decomposition structure [C,S] by soft or hard thresholding
defined in vectors N and T.
wthcoef2 is a two-dimensional denoising and compression
oriented function.
NC = wthcoef2('type',C,S,N)
returns the horizontal, vertical, or diagonal coefficients obtained from
[C,S] by setting all the coefficients of detail levels
defined in N to zero.
NC = wthcoef2('a',C,S)
returns the coefficients obtained by setting approximation coefficients to
zero.
NC = wthcoef2('t',C,S,N,T,SORH)
returns the detail coefficients obtained from the wavelet decomposition structure
[C,S] by soft or hard thresholding defined in vectors
N and T.
[NC,S] is the modified wavelet decomposition structure.
Perform a level 2 wavelet decomposition of the image using the haar wavelet.
[C,S]=wavedec2(X,2,'haar');
Return the vertical coefficients obtained from the wavelet decomposition structure, by soft thresholding defined in the thresholding vectors N =[1 2] and T=[2 4]. N specifies the detail levels, and T specifies the thresholds.
C — Wavelet decomposition vector real-valued vector
Wavelet decomposition vector. The vector C contains
the approximation and detail coefficients organized by level. The function
uses the bookkeeping matrix S to parse
C.
The vector C is organized as
A(N),
H(N),
V(N),
D(N),
H(N-1),
V(N-1),
D(N-1), …,
H(1), V(1), D(1),
where A, H, V, and
D are each a row vector. Each vector is the
column-wise storage of a matrix.
Bookkeeping matrix. The matrix S contains the
dimensions of the wavelet coefficients by level and the function uses it to
parse the wavelet decomposition vector C.
S(1,:) = size of approximation
coefficients(N).
S(i,:) = size of detail
coefficients(N-i+2) for
i = 2, ...N+1 and
S(N+2,:) = size(X).
The following diagram shows the relationship between
C and S in the wavelet
decomposition of a 512-by-512 matrix.
When X represents an indexed image, the output arrays
cA, cH, cV, and
cD are m-by-n
matrices. When X represents a truecolor image, it is an
m-by-n-by-3 array, where each
m-by-n matrix represents a red,
green, or blue color plane concatenated along the third dimension. The size
of vector C and the size of matrix
S depend on the type of the analyzed image.
For a truecolor image, the decomposition vector C and
the corresponding bookkeeping matrix S can be
represented as shown.
Threshold vector, specified by a size 1 ≤ N(i)
≤ size(S,1)-2. N
contains the detail levels to be thresholded and T the
corresponding thresholds.
T — Threshold vector nonnegative vectors
Threshold vector, specified as a nonnegative vector.
N and T must be of the same length.
N contains the detail levels to be thresholded and
T the corresponding thresholds.
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