Wenyi Wang

Bio: Wenyi Wang is an academic researcher from University of Ottawa. The author has contributed to research in topics: Video quality & Video post-processing. The author has an hindex of 1, co-authored 1 publications receiving 9 citations.

Hiding depth information in compressed 2D image/video using reversible watermarking

Abstract: In this paper, a novel joint coding scheme is proposed for 3D media content including stereo images and multiview-plus-depth (MVD) video for the purpose of depth information hiding. The depth information is an image or image channel which reveals the distance of scene objects' surfaces from a viewpoint. With the concern of copyright protection, access control and coding efficiency for 3D content, we propose to hide the depth information into the texture image/video by a reversible watermarking algorithm called Quantized DCT Expansion (QDCTE). Considering the crucial importance of depth information for depth-image-based rendering (DIBR), full resolution depth image/video is compressed and embedded into the texture image/video, and it can be extracted without extra quality degradation other than compression itself. The reversibility of the proposed algorithm guarantees that texture image/video quality will not suffer from the watermarking process even if high payload (i.e. depth information) is embedded into the cover image/video. In order to control the size increase of watermarked image/video, the embedding function is carefully selected and the entropy coding process is also customized according to watermarking strength. Huffman and content-adaptive variable-length coding (CAVLC), which are respectively used for JPEG image and H.264 video entropy encoding, are analyzed and customized. After depth information embedding, we propose a new method to update the entropy codeword table with high efficiency and low computational complexity according to watermark embedding strength. By using our proposed coding scheme, the depth information can be hidden into the compressed texture image/video with little bitstream size overhead while the quality degradation of original cover image/video from watermarking can be completely removed at the receiver side.

IST project ATTEST - an evolutionary and optimised approach on 3D-TV

Abstract: In this paper we will present the concept of a system that allows for an evolutionary introduction of depth perception into the existing 2D digital TV framework. The work is part of the European Information Society Technologies (IST) project “Advanced Three-Dimensional Television System Technologies” (ATTEST), an activity where industries, research centers and universities have joined forces to design a backwardscompatible, flexible and modular broadcast 3D-TV system, where all parts of the 3D processing chain are optimised to one another. This includes content creation, coding and transmission, display and research in human 3D perception, which be will used to guide the development process. The goals of the project comprise the development of a novel broadcast 3D camera, algorithms to convert existing 2D-video material into 3D, a 2Dcompatible coding and transmission scheme for 3D-video using MPEG2/4/7 technologies and the design of two new autostereoscopic displays.

On Computational Aspects of Tchebichef Polynomials for Higher Polynomial Order

Abstract: Tchebichef polynomials (TPs) and their moments are widely used in signal processing due to their remarkable performance in signal analysis, feature extraction, and compression capability. The common problem of the TP is that the coefficients computation is prone to numerical instabilities when the polynomial order becomes large. In this paper, a new algorithm is proposed to compute the TP coefficients (TPCs) for higher polynomial order by combining two existing recurrence algorithms: the three-term recurrence relations in the $n$ -direction and $x$ -direction. First, the TPCs are computed for $x,n=0,1, {\dots },({N}/{2})-1$ using the recurrence in the $x$ -direction. Second, the TPCs for $x=0,1, {\dots },({N}/{2})-1$ and $n=({N}/{2}), ({N}/{2})+1, {\dots },N-1$ based on $n$ and $x$ directions are calculated. Finally, the symmetry condition is applied to calculate the rest of the coefficients for $x=({N}/{2}),({N}/{2})+1, {\dots },N-1$ . In addition to the ability of the proposed algorithm to reduce the numerical propagation errors, it also accelerates the computational speed of the TPCs. The performance of the proposed algorithm was compared to that of existing algorithms for the reconstruction of speech and image signals taken from different databases. The performance of the TPCs computed by the proposed algorithm was also compared with the performance of the discrete cosine transform coefficients for speech compression systems. Different types of speech quality measures were used for evaluation. According to the results of the comparative analysis, the proposed algorithm makes the computation of the TP superior to that of conventional recurrence algorithms when the polynomial order is large.

Signal compression and enhancement using a new orthogonal-polynomial-based discrete transform

Abstract: Discrete orthogonal functions are important tools in digital signal processing. These functions received considerable attention in the last few decades. This study proposes a new set of orthogonal functions called discrete Krawtchouk–Tchebichef transform (DKTT). Two traditional orthogonal polynomials, namely, Krawtchouk and Tchebichef, are combined to form DKTT. The theoretical and mathematical frameworks of the proposed transform are provided. DKTT was tested using speech and image signals from a well-known database under clean and noisy environments. DKTT was applied in a speech enhancement algorithm to evaluate the efficient removal of noise from speech signal. The performance of DKTT was compared with that of standard transforms. Different types of distance (similarity index) and objective measures in terms of image quality, speech quality, and speech intelligibility assessments were used for comparison. Experimental tests show that DKTT exhibited remarkable achievements and excellent results in signal compression and speech enhancement. Therefore, DKTT can be considered as a new set of orthogonal functions for futuristic applications of signal processing.

Reliable Recurrence Algorithm for High-Order Krawtchouk Polynomials

Abstract: Krawtchouk polynomials (KPs) and their moments are promising techniques for applications of information theory, coding theory, and signal processing. This is due to the special capabilities of KPs in feature extraction and classification processes. The main challenge in existing KPs recurrence algorithms is that of numerical errors, which occur during the computation of the coefficients in large polynomial sizes, particularly when the KP parameter (p) values deviate away from 0.5 to 0 and 1. To this end, this paper proposes a new recurrence relation in order to compute the coefficients of KPs in high orders. In particular, this paper discusses the development of a new algorithm and presents a new mathematical model for computing the initial value of the KP parameter. In addition, a new diagonal recurrence relation is introduced and used in the proposed algorithm. The diagonal recurrence algorithm was derived from the existing n direction and x direction recurrence algorithms. The diagonal and existing recurrence algorithms were subsequently exploited to compute the KP coefficients. First, the KP coefficients were computed for one partition after dividing the KP plane into four. To compute the KP coefficients in the other partitions, the symmetry relations were exploited. The performance evaluation of the proposed recurrence algorithm was determined through different comparisons which were carried out in state-of-the-art works in terms of reconstruction error, polynomial size, and computation cost. The obtained results indicate that the proposed algorithm is reliable and computes lesser coefficients when compared to the existing algorithms across wide ranges of parameter values of p and polynomial sizes N. The results also show that the improvement ratio of the computed coefficients ranges from 18.64% to 81.55% in comparison to the existing algorithms. Besides this, the proposed algorithm can generate polynomials of an order ∼8.5 times larger than those generated using state-of-the-art algorithms.

Chaotic Reversible Watermarking Method Based on IWT with Tamper Detection for Transferring Electronic Health Record

Abstract: Health IoT deals with sensitive medical information of patients, therefore security concerns need to be addressed. Confidentiality of Electronic Health Record (EHR) and privacy are two important security requirements for IoT based healthcare systems. Recently, watermarking algorithms as an efficient response to these requirements is in the spotlight. Further, as smart city-based applications have to react to real-time situations, efficient computation is a demand for them. In this paper, a secure, lightweight, reversible, and high capacity watermarking algorithm with tamper detection capability is proposed for IoT based healthcare systems. The scheme has applied Integer Wavelet Transform (IWT) and chaotic map for efficiency and increasing security. EHR is encrypted and then embedded into the Least Significant Bits (LSB) of wavelet coefficients of medical images. The proposed method has been extensively tested for various color and grayscale commonly used medical and general images. Investigations on experimental results and criterions such as Peak Signal to Noise Ratio (PSNR) and Bit Error Ratio (BER) above 45.41 dB and 0.04, respectively, for payload of 432,538 bits indicate that the proposed method, besides providing security, being reversible, tamper detection capability, and high embedding capacity, has high imperceptibility and adequate resistance against different types of attacks.