Hello Cev,
You can use the 'dct2' function for compressing hyperspectral images. To compress hyperspectral images using the `dct2` function in MATLAB, please follow these steps:
- Load your hyperspectral image, which is typically a 3D array with dimensions representing height, width, and spectral bands. For each band, apply the 2D Discrete Cosine Transform (DCT) using `dct2`.
- Quantize the DCT coefficients by dividing them by a quantization factor and rounding the result, which reduces precision and achieves compression. Set small coefficients below a certain threshold to zero to further compress the data.
- To reconstruct the image, apply the inverse DCT using `idct2` on the quantized coefficients for each band.
You can then calculate the compression ratio by comparing the size of the original image to the number of non-zero elements in the compressed image. Adjust the quantization factor and threshold to balance between compression efficiency and image quality.
The 'dct2' and 'idct2' functions were introduced before R2006a and should be available in your release. Please refer the following documentations for more information:
- https://www.mathworks.com/help/images/ref/dct2.html
- https://www.mathworks.com/help/images/ref/idct2.html
I hope this helps!
