Digital Watermarking Implementation Using DWT (Discrete Wavelet Transform)

This documentation presents a digital watermarking technique utilizing the Discrete Wavelet Transform (DWT) approach. The implementation includes extensive inline comments designed to help developers comprehend the code structure and algorithmic workflow effectively. The methodology employs multi-resolution analysis through DWT decomposition, typically implemented using wavelet families like Haar or Daubechies. Key functions include: - dwt2() for 2D discrete wavelet transformation - idwt2() for inverse transformation to reconstruct watermarked images - Coefficient modification algorithms for embedding watermarks in selected subbands (HL, LH, or HH) The code demonstrates robust watermark embedding through frequency domain manipulation, where watermark data is inserted into mid-frequency coefficients to balance invisibility and robustness. Extraction routines reverse this process by detecting and reconstructing the embedded watermark from transformed coefficients. Detailed comments explain each processing stage - from image preprocessing and wavelet decomposition to coefficient thresholding and inverse transformation. This structured approach facilitates understanding of how DWT properties (time-frequency localization) enhance watermark resilience against common attacks while maintaining visual quality.