Distributed coding of endoscopic video

Triggered by the challenging prerequisites of wireless capsule endoscopic video technology, this paper presents a novel distributed video coding (DVC) scheme, which employs an original hash-based side-information creation method at the decoder. In contrast to existing DVC schemes, the proposed codec generates high quality side-information at the decoder, even under the strenuous motion conditions encountered in endoscopic video. Performance evaluation using broad endoscopic video material shows that the proposed approach brings notable and consistent compression gains over various state-of-the-art video codecs at the additional benefit of vastly reduced encoding complexity

Causal Analysis for Performance Modeling of Computer Programs

Causal modeling and the accompanying learning algorithms provide useful extensions for in-depth statistical investigation and automation of performance modeling. We enlarged the scope of existing causal structure learning algorithms by using the form-free information-theoretic concept of mutual information and by introducing the complexity criterion for selecting direct relations among equivalent relations. The underlying probability distribution of experimental data is estimated by kernel density estimation. We then reported on the benefits of a dependency analysis and the decompositional capacities of causal models. Useful qualitative models, providing insight into the role of every performance factor, were inferred from experimental data. This paper reports on the results for a LU decomposition algorithm and on the study of the parameter sensitivity of the Kakadu implementation of the JPEG-2000 standard. Next, the analysis was used to search for generic performance characteristics of the applications

Progressively refined Wyner-Ziv video coding for visual sensors

Wyner-Ziv video coding constitutes an alluring paradigm for visual sensor networks, offering efficient video compression with low complexity encoding characteristics. This work presents a novel hash-driven Wyner-Ziv video coding architecture for visual sensors, implementing the principles of successively refined Wyner-Ziv coding. To this end, so-called side-information refinement levels are constructed for a number of grouped frequency bands of the discrete cosine transform. The proposed codec creates side-information by means of an original overlapped block motion estimation and pixel-based multihypothesis prediction technique, specifically built around the pursued refinement strategy. The quality of the side-information generated at every refinement level is successively improved, leading to gradually enhanced Wyner-Ziv coding performance. Additionally, this work explores several temporal prediction structures, including a new hierarchical unidirectional prediction structure, providing both temporal scalability and low delay coding. Experimental results include a thorough evaluation of our novel Wyner-Ziv codec, assessing the impact of the proposed successive refinement scheme and the supported temporal prediction structures for a wide range of hash configurations and group of pictures sizes. The results report significant compression gains with respect to benchmark systems in Wyner-Ziv video coding (e. g., up to 42.03% over DISCOVER) as well as versus alternative state-of-the-art schemes refining the side-information

Wyner-Ziv video coding for wireless lightweight multimedia applications

Wireless video communications promote promising opportunities involving commercial applications on a grand scale as well as highly specialized niche markets. In this regard, the design of efficient video coding systems, meeting such key requirements as low power, mobility and low complexity, is a challenging problem. The solution can be found in fundamental information theoretic results, which gave rise to the distributed video coding (DVC) paradigm, under which lightweight video encoding schemes can be engineered. This article presents a new hash-based DVC architecture incorporating a novel motion-compensated multi-hypothesis prediction technique. The presented method is able to adapt to the regional variations in temporal correlation in a frame. The proposed codec enables scalable Wyner-Ziv video coding and provides state-of-the-art distributed video compression performance. The key novelty of this article is the expansion of the application domain of DVC from conventional video material to medical imaging. Wireless capsule endoscopy in particular, which is essentially wireless video recording in a pill, is proven to be an important application field. The low complexity encoding characteristics, the ability of the novel motion-compensated multi-hypothesis prediction technique to adapt to regional degrees of temporal correlation (which is of crucial importance in the context of endoscopic video content), and the high compression performance make the proposed distributed video codec a strong candidate for future lightweight (medical) imaging applications