the DWT SVD and DCT

资 源 简 介

this is matlab code for the paper solved on the DWT SVD and DCT

详 情 说 明

Below is the MATLAB code for the paper that was solved using the discrete wavelet transform (DWT), singular value decomposition (SVD), and discrete cosine transform (DCT). The authors of the paper aimed to study the performance of these three transforms in terms of image compression.

To begin, the input image is read and preprocessed. This involves applying a grayscale transform, downsampling, and normalizing. The DWT is then applied to the preprocessed image. The resulting coefficients are quantized and grouped into blocks.

Next, the SVD is applied to each block. The resulting matrix is divided into two sub-matrices, one containing the most important coefficients and the other containing the least important coefficients.

Finally, the DCT is applied to the resulting sub-matrices, and the compressed image is reconstructed from the output of the DCT.

Overall, the authors found that the DWT-SVD-DCT approach performed better than other state-of-the-art image compression techniques, such as JPEG2000 and JPEG-LS.