Date of Award


Degree Type

Closed Dissertation

Degree Name

Doctor of Philosophy (PhD)


Computer Science

First Advisor

Dr. Michael Weeks - Chair

Second Advisor

Dr. Saeid Belkasim

Third Advisor

Dr. Robert Harrison

Fourth Advisor

Dr. Ephraim McLean


Safeguarding creative content in a digital form has become increasingly difficult. It is progressively easier to copy, modify and redistribute digital media, which causes great declines in business profits. For example, the International Federation of the Phonographic Industry estimates that in 2001 the worldwide sales of pirated music CDs were 475 million US dollars. While a large amount of time and money is committed to creating intellectual property, legal means have not proven to be sufficient for the protection of this property. Digital watermarking is a steganographic technique that has been proposed as a possible solution to this problem. A digital watermark hides embedded information about the origin, status, owner and/or destination of the data, often without the knowledge of the viewer or user. This dissertation examines a technique for digital watermarking which utilizes properties of the Discrete Wavelet Transform (DWT). Research has been done in this field, but which wavelet family is superior is not adequately addressed. This dissertation studies the influence of the wavelet family when using a blind, nonvisible watermark in digital media. The digital watermarking algorithm uses a database of multiple images with diverse properties. Various watermarks are embedded. Eight different families of wavelets with dissimilar properties are compared. How effective is each wavelet? To objectively measure the success of the algorithm, the influence of the mother wavelet, the imperceptibility of the embedded watermark and the readability of the extracted watermark, the Peak Signal-to-Noise Ratio and the Image Quality Index for each wavelet family and image are obtained. Two common categories of digital watermarking attacks are removing the watermark and rendering the watermark undetectable. To simulate and examine the effect of attacks on the images, noise is added to the image data. Also, to test the effect of reducing an image in size, each image containing the embedded watermark is compressed. The dissertation asks the questions: “Is the wavelet family chosen to implement the algorithm for a blind, nonvisible watermark in digital images of consequence? If so, which family is superior?” This dissertation conclusively shows that the Haar transform is the best for blind, non-visible digital watermarking.