DWT Domain Fragile Watermarking

The fragile watermarking implementation based on Discrete Wavelet Transform (DWT) domain was my major coursework project for the digital image processing course. Fragile watermarking represents a technique for embedding information into digital images to protect their integrity and security. In this project, I utilized discrete wavelet transform as the foundation for watermark embedding, performing transformation and adjustment operations on the image to embed watermark information into the detail coefficients of the frequency domain. This approach involves implementing algorithms that decompose the image into multiple frequency subbands (LL, LH, HL, HH) using wavelet filters like Haar or Daubechies, then modifying specific high-frequency coefficients to carry the watermark payload. The implementation typically includes key functions for DWT decomposition, coefficient modification with controlled embedding strength, and inverse DWT reconstruction. Through this methodology, watermark information can be embedded into images without compromising visual quality, while enabling accurate watermark detection and extraction through coefficient analysis and comparison algorithms. This coursework project not only deepened my understanding of DWT principles and applications but also significantly enhanced my practical skills in digital image processing, particularly in implementing frequency-domain transformation techniques and developing robust watermarking systems.