2-D approximation coefficients extraction
A=appcoef2(C,S,wname,[N]) A=appcoef2(C,S,Lo_R,Hi_R,[N])
wavelet name, haar( "haar"), daubechies ("db1" to "db36"), coiflets ("coif1" to "coif17"), symlets ("sym2" to "sym20"), legendre ("leg1" to "leg9"), bathlets("bath4.0" to "bath4.15" and "bath6.0" to "bath6.15"), dmey ("dmey"), beyklin ("beylkin"), vaidyanathan ("vaidyanathan"), biorthogonal B-spline wavelets ("bior1.1" to "bior6.8"), "rbior1.1" to "rbior6.8"
extracted approximation coefficients
lowpass synthesis filter
highpass syntheis filter
coefficent array
size array
restruction level with N<=length(L)-2
appcoef2 can be used for extraction or reconstruction of approximation coeffient at level N after a multiple level decompostion. Extension mode is stored as a global variable and could be changed with dwtmode. If N is omitted, the maximum level (length(L)-2) is used.
The length of A depends on the level N.
C and L can be generated using wavedec2.
load(get_swt_path()+"demos/image/woman.dat"); [C,S]=wavedec2(X,3,'db2'); A1=appcoef2(C,S,'db2',1); A2=appcoef2(C,S,'db2',2); A3=appcoef2(C,S,'db2',3); scf();clf(); f=gcf();f.color_map=gray(256); subplot(221) Matplot(X); a=gca();a.tight_limits="on"; title("original"); subplot(222) Matplot(A1); a=gca();a.tight_limits="on"; title("approximation level 1"); subplot(223) Matplot(A2); a=gca();a.tight_limits="on"; title("approximation level 2"); subplot(224) Matplot(A3); a=gca();a.tight_limits="on"; title("approximation level 3"); | ![]() | ![]() |