Keywords : quantization

Digital Image Watermarking Scheme Using Discrete Wavelet Transform Domain, Quantization, and Genetic Algorithm

Nasseer Basheer; Shaymaa S Abdulsalam

AL-Rafidain Journal of Computer Sciences and Mathematics, 2013, Volume 10, Issue 1, Pages 13-27
DOI: 10.33899/csmj.2013.163421

Protection of digital multimedia content has become an increasingly important issue for content owners and service providers. Watermarking is identified as a major means to achieve copyright protection. The algorithm proposed in this work, is to use a blind watermarking scheme based on the Discrete Wavelet Transform (DWT). Watermark components are embedded in the LL subband of the 4th DWT level of the host image by quantizing coefficients of the LL subband to improve the watermark robustness. The Genetic Algorithm (GA) is used for optimizing the quantization step size parameter, and the strength of factors. The host image used is a 512×512 gray scale image and the watermark image is a 32×32 binary logo. The proposed scheme was tested against mostly known threats and it proves to give good robustness. Also, it still gives a high quality watermarked image. MATLAB Program was used to perform the watermarking task.

Comparison on Color Quantization Techniques

Alyaa taqi

AL-Rafidain Journal of Computer Sciences and Mathematics, 2008, Volume 5, Issue 1, Pages 95-115
DOI: 10.33899/csmj.2008.163965

Due to the fast and high development in computer technology and the reflection of this development on digital images ,many image processing algorithms became in need to initialization steps for the image before starting the actual operations of the algorithms and the program. Image quantization is one of the important operations in image processing field and it is the first step in  many digital image applications.
This technique is based on taking the best colors  from the original image and produce a new image with a new quality with less colors and with small error ratio. There are many image quantization methods ,but this research focuses on studying three different methods of image quantization and compares  them. These methods are:

Quantization by mask
Uniform Quantization
Half toning Quantization

After programming the methods we could reach a high degree of clarity in image after reducing  its color. The research was applied on different types of images to find the best method for each image  with small error ratio and that depends on the contents and on color distributions in the image .(Matlab7) was used for programming these methods.