Gradually people are motivated to embed information such as owner info, date, time, camera settings, event/occasion of the image, image title, or even secret message in the digital images for value-added functionalities and possibly secret communication. A novel sample-based methods are proposed to embed some information bits in the JPEG compressed domain. The proposed method called J-Mark embeds the information bits in the DCT coefficients with significant energy in the selected blocks significant masking properties. Spread spectrum technique (SST) is widely adopted for vector-based image and video watermarking in the past few years. Four novel techniques are proposed to embed watermarks for different purposes. The first one call Single Watermark Embedding (SWE) is use to embed a wate...[ Read more ]

Gradually people are motivated to embed information such as owner info, date, time, camera settings, event/occasion of the image, image title, or even secret message in the digital images for value-added functionalities and possibly secret communication. A novel sample-based methods are proposed to embed some information bits in the JPEG compressed domain. The proposed method called J-Mark embeds the information bits in the DCT coefficients with significant energy in the selected blocks significant masking properties. Spread spectrum technique (SST) is widely adopted for vector-based image and video watermarking in the past few years. Four novel techniques are proposed to embed watermarks for different purposes. The first one call Single Watermark Embedding (SWE) is use to embed a watermark bit sequence in digital images using two secret keys. The second technique called Multiple Watermark Embedding (MWE) extends SWE to embed multiple watermarks simultaneously in the same watermark space while minimizing the watermark energy. The third technique called Iterative Watermark Embedding (IWE) embeds watermarks in JPEG-compressed images. The proposed iterative approach can prevent largely the potential removal of watermarks in the JPEG recompression process. The fourth technique called Direct JPEG Watermark Embedding (DJWE) is an extension of the IWE. DJWE embeds the watermarks with lower computation complexity then IWE and uses the Human Visual System (HVS) model to prioritize the coefficients to be altered to achieve good visual quality.

Two techniques for watermarking capacity estimation are proposed. The first technique estimates the capacity for JPEG-to-JPEG image watermarking (J2J). In J2J image watermarking, the input is a JPEG image file and, after watermark embedding, the image is JPEG-compressed such that the output file is also a JPEG file. The second technique is an extension of the first technique to JPEG2000-to-JPEG2000 (J2K-2-J2K) watermarking. In J2K-2-J2K, the input is a JPEG2000 image file and, after watermark embedding, the image is JPEG2000-compressed using the same quantization factors. The Watson’s Discrete Wavelet Transform (DWT) HVS model is used to estimate the JND of each Discrete Wavelet Transform (DWT) coefficients. The proposed techniques do not assume any specific watermarking method and thus would apply to any watermarking methods in the J2J and J2K-2-J2K framework.