The IDWT2D function is the inverse of DWT2D (ML Engine); that is, IDWT2D applies inverse wavelet transforms on multiple sequences simultaneously. IDWT2D takes as input the output table and meta table output by DWT2D and outputs the sequences as 2-dimensional matrixes. (Because the IDWT2D output is comparable to the DWT2D input, the inverse transformation is also called the reconstruction.)
This is a typical IDWT2D use case:
- Apply DWT2D to 2-dimensional sequences to create the coefficients of the matrixes and corresponding metadata.
- Filter the coefficients by methods appropriate for the objects (for example, minimum threshold or top n coefficients), compressing the original matrixes.
- Apply IDWT to the filtered coefficients to reconstruct the sequences.
- Compare the reconstructed matrixes to their original counterparts.