lwt2
Description
[
performs the 2-D lifting wavelet transform (LWT) of the real- or complex-valued
matrix ll
,lh
,hl
,hh
] = lwt2(x
)x
using the db1
wavelet. The function
performs the decomposition first along the rows in x
and then
along the columns. The default decomposition level depends on the size of
x
. For more information, see Level. The function returns the approximation coefficients at the
coarsest scale and the horizontal, vertical, and diagonal detail coefficients by
level.
If x
is a single-precision input, the numeric type of the
coefficients is single precision. Otherwise, the numeric type is double
precision.
[___] = lwt2(
specifies options using one or more name-value arguments. For example,
x
,Name=Value
)lwt2(x,Wavelet="db2",Level=3)
performs 2-D LWT using the
db2
wavelet and a level 3 decomposition.
Examples
Input Arguments
Output Arguments
Algorithms
At each stage of a 2-D wavelet decomposition, the approximation coefficients at level j are decomposed into four components: the approximation at level j+1 and the details in three orientations (horizontal, vertical, and diagonal). Each component is the result of convolving the rows and columns of the level j approximation with the appropriate combination of lowpass and highpass filters, LoD and HiD, respectively, followed by downsampling:
Approximation — Convolve the rows and columns with a lowpass filter (
ll
)Horizontal — Convolve the rows with a lowpass filter, and convolve the columns with a highpass filter (
lh
)Vertical — Convolve the rows with a highpass filter, and convolve the columns with a lowpass filter (
hl
)Diagonal — Convolve the rows and columns with a highpass filter (
hh
)
The following chart describes the basic decomposition steps.
where
— Downsample columns: keep the even-indexed columns
— Downsample rows: keep the even-indexed rows
— Convolve the rows of the entry with filter X
— Convolve the columns of the entry with filter X
The decomposition is initialized by setting the approximation coefficients equal to the image s: cA0 = s.
References
[1] Daubechies, Ingrid. Ten Lectures on Wavelets. CBMS-NSF Regional Conference Series in Applied Mathematics 61. Philadelphia, Pa: Society for Industrial and Applied Mathematics, 1992.
[2] Mallat, S.G. “A Theory for Multiresolution Signal Decomposition: The Wavelet Representation.” IEEE Transactions on Pattern Analysis and Machine Intelligence 11, no. 7 (July 1989): 674–93. https://doi.org/10.1109/34.192463.
[3] Strang, Gilbert, and Truong Nguyen. Wavelets and Filter Banks. Rev. ed. Wellesley, Mass: Wellesley-Cambridge Press, 1997.
[4] Sweldens, Wim. “The Lifting Scheme: A Construction of Second Generation Wavelets.” SIAM Journal on Mathematical Analysis 29, no. 2 (March 1998): 511–46. https://doi.org/10.1137/S0036141095289051.
Extended Capabilities
Version History
Introduced in R2021bSee Also
ilwt2
| lwtcoef2
| haart2
| ihaart2
| liftingScheme