Journal ArticleDOI
Spread spectrum image steganography
TLDR
A new method of digital Steganography, entitled spread spectrum image steganography (SSIS), which hides and recovers a message of substantial length within digital imagery while maintaining the original image size and dynamic range.Abstract:
We present a new method of digital steganography, entitled spread spectrum image steganography (SSIS). Steganography, which means "covered writing" in Greek, is the science of communicating in a hidden manner. Following a discussion of steganographic communication theory and review of existing techniques, the new method, SSIS, is introduced. This system hides and recovers a message of substantial length within digital imagery while maintaining the original image size and dynamic range. The hidden message can be recovered using appropriate keys without any knowledge of the original image. Image restoration, error-control coding, and techniques similar to spread spectrum are described, and the performance of the system is illustrated. A message embedded by this method can be in the form of text, imagery, or any other digital signal. Applications for such a data-hiding scheme include in-band captioning, covert communication, image tamperproofing, authentication, embedded control, and revision tracking.read more
Citations
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Journal Article
Dynamic Collage Steganography on Images
TL;DR: A new generalized collage steganography, an augmentation of collage Steganographic method, is presented to improve the capacity problem since the limitation of the traditional method is capacity.
Proceedings ArticleDOI
A sparse representation based approach for steganography
Ribhu,Debashis Ghosh +1 more
TL;DR: The proposed method hides data within an audio clip or an image without compromising on their perceived qualities and is not robust to any sort of lossy processing like compression, cropping, etc.
Proceedings ArticleDOI
Two algorithms for compressing noise like signals
TL;DR: This paper introduces a two new compression technique that compresses the random data like noise with reference to know pseudo noise sequence generated using a key and developed a representation model for digital media using the pseudo noise signals.
Motion Vectors Used in Compressed Video
TL;DR: This paper targets the motion vectors used to encode and reconstruct both the forward predictive (P)-frame and bidirectional (B)-frames in compressed video and proposes a greedy adaptive threshold to achieve robustness while maintaining a low prediction error level.
References
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Journal ArticleDOI
De-noising by soft-thresholding
TL;DR: The authors prove two results about this type of estimator that are unprecedented in several ways: with high probability f/spl circ/*/sub n/ is at least as smooth as f, in any of a wide variety of smoothness measures.
Book
Fundamentals of digital image processing
TL;DR: This chapter discusses two Dimensional Systems and Mathematical Preliminaries and their applications in Image Analysis and Computer Vision, as well as image reconstruction from Projections and image enhancement.
Journal ArticleDOI
Error bounds for convolutional codes and an asymptotically optimum decoding algorithm
TL;DR: The upper bound is obtained for a specific probabilistic nonsequential decoding algorithm which is shown to be asymptotically optimum for rates above R_{0} and whose performance bears certain similarities to that of sequential decoding algorithms.
Journal ArticleDOI
Secure spread spectrum watermarking for multimedia
TL;DR: It is argued that insertion of a watermark under this regime makes the watermark robust to signal processing operations and common geometric transformations provided that the original image is available and that it can be successfully registered against the transformed watermarked image.