Oscar C. Au

Bio: Oscar C. Au is an academic researcher from Hong Kong University of Science and Technology. The author has contributed to research in topics: Motion estimation & Motion compensation. The author has an hindex of 40, co-authored 491 publications receiving 7493 citations. Previous affiliations of Oscar C. Au include Wilmington University & Huawei.

Video Error Concealment Using Spatio-Temporal Boundary Matching and Partial Differential Equation

Abstract: Error concealment techniques are very important for video communication since compressed video sequences may be corrupted or lost when transmitted over error-prone networks. In this paper, we propose a novel two-stage error concealment scheme for erroneously received video sequences. In the first stage, we propose a novel spatio-temporal boundary matching algorithm (STBMA) to reconstruct the lost motion vectors (MV). A well defined cost function is introduced which exploits both spatial and temporal smoothness properties of video signals. By minimizing the cost function, the MV of each lost macroblock (MB) is recovered and the corresponding reference MB in the reference frame is obtained using this MV. In the second stage, instead of directly copying the reference MB as the final recovered pixel values, we use a novel partial differential equation (PDE) based algorithm to refine the reconstruction. We minimize, in a weighted manner, the difference between the gradient field of the reconstructed MB in current frame and that of the reference MB in the reference frame under given boundary condition. A weighting factor is used to control the regulation level according to the local blockiness degree. With this algorithm, the annoying blocking artifacts are effectively reduced while the structures of the reference MB are well preserved. Compared with the error concealment feature implemented in the H.264 reference software, our algorithm is able to achieve significantly higher PSNR as well as better visual quality.

Video Coding on Multicore Graphics Processors

Abstract: In this article, we investigate using multi-core graphics processing units (GPUs) for video encoding and decoding. After an overview of video coding and GPUs, we review some previous work on structuring video coding modules so that the massive parallel processing capability of GPUs can be harnessed. We also review previous work on partitioning the video decoding flow between the central processing unit (CPU) and GPU. After that, we discuss in detail a GPU based fast motion estimation to illustrate some design considerations in using GPUs for video coding, and the tradeoff between speedup and rate-distortion performance. Our results highlight the importance to expose as much data parallelism as possible in designing algorithms for GPUs.

Predictive motion vector field adaptive search technique (PMVFAST) - enhancing block based motion estimation

Abstract: Motion Estimation (ME) is an important part of most video encoding systems, since it could significantly affect the output quality of an encoded sequence. Unfortunately this feature requires a significant part of the encoding time especially when using the straightforward Full Search (FS) algorithm. In this paper a new algorithm is presented named as the Predictive Motion Vector Field Adaptive Search Technique (PMVFAST), which significantly outperforms most if not all other previously proposed algorithms in terms of Speed Up performance. In addition, the output quality of the encoded sequence in terms of PSNR is similar to that of the Full Search algorithm. The proposed algorithm relies mainly upon very robust and reliable predictive techniques and early termination criteria, which make use of parameters adapted to the local characteristics of a frame. Our experiments verify the superiority of the proposed algorithm, not only versus several other well-known fast algorithms, but also in many cases versus even the Full Search algorithm.

Data hiding in halftone images by stochastic error diffusion

Abstract: We propose a novel method called DHSED (data hiding stochastic error diffusion) to hide binary visual patterns in two error diffused halftone images. While one halftone image is only a regular error diffused image, stochastic error diffusion is applied to the other image to generate special stochastic characteristics with respect to the first image such that the visual pattern would appear when the two halftone images are overlaid Simulation results show that the two halftone images have good visual quality, and the hidden pattern appears with "normal" and "lower-than-normal" intensity when the two halftone images are overlaid.

Lossless Visible Watermarking

Abstract: The embedding distortion of visible watermarking is usually larger than that of invisible watermarking. In order to maintain the signal fidelity after the watermark extraction, "lossless" property is highlighted in the visible watermarking. In this paper, we propose two lossless visible watermarking algorithms, Pixel Value Matching Algorithm (PVMA) and Pixel Position Shift Algorithm (PPSA). PVMA uses the bijective intensity mapping function to watermark a visible logo whereas PPSA uses circular pixel shift to improve the visibility of the watermark in the high variance region. For the application of medical and military, as they are sensitive to distortion, PVMA and PPSA can be used to insert a visible logo to prevent unauthorized use.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Digital Watermarking

Abstract: Digital watermarking is a key ingredient to copyright protection. It provides a solution to illegal copying of digital material and has many other useful applications such as broadcast monitoring and the recording of electronic transactions. Now, for the first time, there is a book that focuses exclusively on this exciting technology. Digital Watermarking covers the crucial research findings in the field: it explains the principles underlying digital watermarking technologies, describes the requirements that have given rise to them, and discusses the diverse ends to which these technologies are being applied. As a result, additional groundwork is laid for future developments in this field, helping the reader understand and anticipate new approaches and applications.

Digital Watermarking and Steganography

Abstract: Digital audio, video, images, and documents are flying through cyberspace to their respective owners. Unfortunately, along the way, individuals may choose to intervene and take this content for themselves. Digital watermarking and steganography technology greatly reduces the instances of this by limiting or eliminating the ability of third parties to decipher the content that he has taken. The many techiniques of digital watermarking (embedding a code) and steganography (hiding information) continue to evolve as applications that necessitate them do the same. The authors of this second edition provide an update on the framework for applying these techniques that they provided researchers and professionals in the first well-received edition. Steganography and steganalysis (the art of detecting hidden information) have been added to a robust treatment of digital watermarking, as many in each field research and deal with the other. New material includes watermarking with side information, QIM, and dirty-paper codes. The revision and inclusion of new material by these influential authors has created a must-own book for anyone in this profession. *This new edition now contains essential information on steganalysis and steganography *New concepts and new applications including QIM introduced *Digital watermark embedding is given a complete update with new processes and applications