A secure and robust digital image watermarking scheme using repetition codes for copyright protection

A Novel Compressed Encrypted and Encoded Watermark Embedding Scheme for Digital Images

“…In this paper eight different "n" values such as 3, 5, 7, 9, 11, 13, 15 and 17 are chosen to study the performance. As higher the "n" value in (n,1) repetition code introduces more redundancy, But improves robustness of watermark against random noise [13] [15]. Also repetition code is a simple encoding technique, computational time and complexity involved in embedding process is low compared to well known error control encoding schemes [16].…”

“…Hence for (n, 1) repetition code, the required number of pixels in the cover image is "n" times the number of pixels of the compressed watermark. However increase in the value of n in (n,1) repetition code improves the robustness of the extracted watermark from watermarked image in the presence of noise [13] [15]. In this paper size of the cover image is 256×256 = 65536 pixels and size of the watermark image is 50×100 = 5000 is chosen.…”

“…Perceptual quality of watermarked image is better in case of proposed LSB and SLSB embedding scheme compared to SLSB embedding scheme alone. However the value of "n" in (n, 1) repetition code is completely depends on the type of channel and severity of noise [13][14] [15].…”

“…Many researchers have used transformation techniques such as Discrete Cosine Transform (DCT) or Discrete Wavelet Transform (DWT) for obtaining robustness against compression and signal processing attacks. However, cover image transformation and inverse transformation involves high computation complexity, increased requirement of hardware circuitry and high power consumption when compared to spatial domain techniques [13] [15]. Many researchers have developed algorithms using spatial domain and transform domain techniques [1]- [10].…”

A highly robust medical image watermarking method for medical real-time applications

“…As watermarking in frequency domains are robust they are more complex than spatial domain watermarking, some researchers attempted to design simple robust watermarking. [ 27 28 29 ] On the other hand, some research considers techniques that somehow fall between spatial and transform domains to benefit from both. [ 30 31 32 ]…”