Wavelet Transform Applied to Digital Watermark Steganography

In digital image processing, multiple algorithms can be employed for digital watermark steganography. Among the commonly used techniques are wavelet transform and discrete cosine transform. The wavelet transform algorithm, widely applied in watermark hiding, decomposes images into different frequency components using multi-resolution analysis. Implementation typically involves applying Discrete Wavelet Transform (DWT) through functions like wavedec2() in MATLAB, embedding watermark information into high-frequency subbands (HL, LH, HH) or low-frequency approximations (LL) to achieve image protection and authentication. The discrete cosine transform approach, another prevalent watermarking method, operates by transforming images into frequency domain using DCT blocks. Code implementation often includes dividing images into 8x8 blocks, applying dct2() function, and modifying specific DCT coefficients to embed watermarks in spatial-frequency domain for image protection and identification. Additionally, various spatial domain algorithms can be utilized for watermark steganography, directly modifying pixel values in spatial domain through techniques like LSB (Least Significant Bit) substitution. These algorithms enable watermark information embedding in images through programmable implementations, ensuring image legitimacy protection and authentication via controlled coefficient modification and frequency domain manipulation.