Hi Maha Lakshmi,
In order to perform a 2D Dual-Tree Discrete Wavelet Transform, you can follow the below steps:
Load the Image:
Read the image that you want to process. Convert it to grayscale if it is in color, as wavelet transforms are typically applied to single-channel images.
I = imread('example.jpg');
if size(I, 3) == 3
I = rgb2gray(I);
end
I = double(I);
Set Up Wavelet Filters:
Define or load the wavelet filters for the dual-tree DWT. The transform uses two sets of filters: one for the real part and another for the imaginary part.
[Faf, Fsf] = FSfarras(); % Filters for the first stage
[af, sf] = dualfilt1(); % Filters for subsequent stages
Perform the 2D Dual-Tree DWT:
Apply the dual-tree transform to the image. This involves decomposing the image using both the real and imaginary filter sets.
J = 3; % Number of decomposition levels
[realTree, imagTree] = dddtree2('cplxdt', I, J, Faf, af);
Visualize the Decomposition:
Display the wavelet coefficients for both the real and imaginary trees at a specific level.
level = 2; % Choose a level to visualize
figure;
subplot(1, 2, 1), imshow(realTree{level}, []), title('Real Tree');
subplot(1, 2, 2), imshow(imagTree{level}, []), title('Imaginary Tree');
Interpret the Results:
Analyze the results to understand the frequency and orientation information captured by the wavelet coefficients.
Refer to the documentation of "dualtree" function to know more about the properties supported: https://www.mathworks.com/help/wavelet/ref/dualtree.html
Hope this helps!
