期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2015
卷号：75
期号：2
出版社：Journal of Theoretical and Applied
摘要：Digital watermarking is an emerging area of research for developing diverse system in order to avoid the repetition and exploitation of secret data. Digital watermarking protects data contents such as images, audio and video files with higher accuracy rate. Recently, several lossy and lossless data compression methods were developed so far but with an additional computation burden making the system not flexible. When implementing, data compression algorithm on digital images, attaining robustness is one of the challenging issues. As the noise ratio is higher, the compressed data are not well reconstructed if compression is done on digital images. In my research work, HAAR Wavelet Orthonormal based Discrete Cosine Data Compression Transformation (DCDCT) is developed to improve the resistant level and to reduce the computational burden on digital images. Initially, the HAAR Wavelet Orthonormal based DCDCT method is composed of two parts namely, watermark compression and decompression operation. In data compression phase, transformation, digitizing and Entropy Encoder operations are carried out. DCDCT method performs the transformation operation through cosine transform, where the embedding data is converted into analog frequency signal components. Secondly, digitizing operation is processed using the Orthonormal wavelet function to perform mapping and improve the resistant level (i.e.,) avoidance of noise rate on data compression. Finally, HAAR wavelet differential Manchester procedure is used on encoding operation. The same three operations are carried out in reverse order for the decompression of data from digital images in DCDCT method. Experiment is conducted on factors such as Peak Signal Noise Ratio (PSNR) Difference, bit error rate and resistance ratio level.
关键词：Discrete Cosine Transform; Digital Watermarking; Data Compression; HAAR Wavelet Transform; Entropy Encoder; Frequency Signal.
