A Convex Optimization Framework for Video Quality and Resolution Enhancement From Multiple Descriptions.

Transmission and compression technologies advancement over the past decade led to a shift of multimedia content towards cloud systems. Multiple copies of the same video are available through numerous distribution systems. Different compression levels, algorithms and resolutions are used to match the requirements of particular applications.

Color digital hologram compression based on matching pursuit.

With the recent widespread interest for head-mounted displays applied to virtual or augmented reality, holography has been considered as an appealing technique for a revolutionary and natural 3D visualization system. However, due to the tremendous amount of data required by holograms and to the very different properties of holographic data compared to common imagery, compression of digital holograms is a highly challenging topic for researchers. In this study, we introduce a novel approach, to the best of our knowledge, for color hologram compression based on matching pursuit using an overcomplete Gabor's dictionary.

Rate Allocation in Predictive Video Coding Using a Convex Optimization Framework.

Optimal rate allocation is among the most challenging tasks to perform in the context of predictive video coding, because of the dependencies between frames induced by motion compensation. In this paper, using a recursive rate-distortion model that explicitly takes into account these dependencies, we approach the frame-level rate allocation as a convex optimization problem. This technique is integrated into the recent HEVC encoder, and tested on several standard sequences.

Reference View Selection in DIBR-Based Multiview Coding.

Augmented reality, interactive navigation in 3D scenes, multiview video, and other emerging multimedia applications require large sets of images, hence larger data volumes and increased resources compared with traditional video services. The significant increase in the number of images in multiview systems leads to new challenging problems in data representation and data transmission to provide high quality of experience on resource-constrained environments. In order to reduce the size of the data, different multiview video compression strategies have been proposed recently.

Adaptive nonseparable vector lifting scheme for digital holographic data compression.

Holographic data play a crucial role in recent three-dimensional imaging as well as microscopic applications. As a result, huge amounts of storage capacity will be involved for this kind of data. Therefore, it becomes necessary to develop efficient hologram compression schemes for storage and transmission purposes.