Ulf Jennehag

Scalable Coding of Plenoptic Images by Using a Sparse Set and Disparities

One of the light field capturing techniques is the focused plenoptic capturing. By placing a microlens array in front of the photosensor, the focused plenoptic cameras capture both spatial and angular information of a scene in each microlens image and across microlens images. The capturing results in a significant amount of redundant information, and the captured image is usually of a large resolution. A coding scheme that removes the redundancy before coding can be of advantage for efficient compression, transmission, and rendering. In this paper, we propose a lossy coding scheme to efficiently represent plenoptic images. The format contains a sparse image set and its associated disparities. The reconstruction is performed by disparity-based interpolation and inpainting, and the reconstructed image is later employed as a prediction reference for the coding of the full plenoptic image. As an outcome of the representation, the proposed scheme inherits a scalable structure with three layers. The results show that plenoptic images are compressed efficiently with over 60 percent bit rate reduction compared with High Efficiency Video Coding intra coding, and with over 20 percent compared with an High Efficiency Video Coding block copying mode.

Increasing bandwidth utilization in next generation IPTV networks

In this paper we present a novel idea regarding transmission of next generation IPTV content. Today IPTV systems utilize a GOP structure to provide stream synchronization points for the clients, these are used when a channel switch occur. Since channel switches made by TV audiences are quite rare it is redundant to send synchronization opportunities in a GOP manner. The proposed design, synchronization frames for channel switching (SFCS), only requests synchronization frames when needed. We present a network traffic analysis model and compare it with simulations. SFCS increases bandwidth utilization compared to traditional GOP system under the presented transmission environment.

Improving Transmission Efficiency in H.264 Based IPTV Systems

In this paper, a novel proposal regarding the transmission of the next generation of live-TV content in an IPTV environment is presented. Today live-TV IP transmission systems utilizes a Group Of Pictures (GOP) structure in order to provide stream synchronization points for the clients. Synchronization points are used when a TV-channel switch occurs. The number of channel switches made by TV audiences have been shown to be rather rare. It is therefore redundant to send synchronization events in a GOP manner. Our proposal, Synchronization Frames for Channel Switching (SFCS), only requests synchronization points when required. Due to channel popularity distributions and the number of connected users, the total number of synchronization requests for a popular channel can increase to a level that makes SFCS less effective than GOP. Therefore, we introduce an SFCS-GOP hybrid. A complete network traffic analysis model, verified by a simple simulation environment, is also presented and the results show that the SFCS-GOP hybrid significantly increases the bandwidth utilization compared to a traditional GOP system

Coding of Focused Plenoptic Contents by Displacement Intra Prediction

A light field is commonly described by a two-plane representation with four dimensions. Refocused 3D contents can be rendered from light field images. A method for capturing these images is using cameras with microlens arrays. A dense sampling of the light field results in large amounts of redundant data. Therefore, an efficient compression is vital for a practical use of these data. In this paper, we propose a displacement intra prediction scheme with a maximum of two hypotheses for the compression of plenoptic contents from focused plenoptic cameras. The proposed scheme is further implemented into High Efficiency Video Coding (HEVC). The work is aiming at efficiently coding plenoptic captured contents without knowing underlying camera geometries. In addition, the theoretical analysis of the displacement intra prediction for plenoptic images is explained; the relationship between the compressed captured images and their rendered quality is also analyzed. Evaluation results show that plenoptic contents can be efficiently compressed by the proposed scheme. Bit rate reduction up to 60% over HEVC is obtained for plenoptic images, and more than 30% is achieved for the tested video sequences.

A scalable coding approach for high quality depth image compression

The distortion by using traditional video encoders (e.g. H.264) on the depth discontinuity can introduce disturbing effects on the synthesized view. The proposed scheme aims at preserving the most significant depth transition for a better view synthesis. Furthermore, it has a scalable structure. The scheme extracts edge contours from a depth image and represents them by chain code. The chain code and the sampled depth values on each side of the edge contour are encoded by differential and arithmetic coding. The depth image is reconstructed by diffusion of edge samples and uniform sub-samples from the low quality depth image. At low bit rates, the proposed scheme outperforms HEVC intra at the edges in the synthesized views, which correspond to the significant discontinuities in the depth image. The overall quality is also better with the proposed scheme at low bit rates for contents with distinct depth transition.

Numerical modeling of transmission errors and video quality of MPEG-2

To efficiently combat the signal loss of MPEG-2 transmission over unreliable networks, priority encoding transmission, unequal packet loss protection and priority dropping techniques have been studied in many papers. Those studies are based on the qualitative analysis of different importance of signals, without quantitative investigation of signal loss effect on video quality. In this paper, MPEG-2 packet loss effect on video quality is quantitatively investigated, a temporal layered signal model is described and evaluated, a quality measure for reconstructed pictures called macroblock impairment ratio is suggested and defined. The investigation and the model are specified for MPEG-2, but the principles and the methods are suitable for any layered video. These are useful for the development of efficient schemes and protocols for packet video transmission over unreliable networks.

Combining Fog Computing with Sensor Mote Machine Learning for Industrial IoT

Digitalization is a global trend becoming ever more important to our connected and sustainable society. This trend also affects industry where the Industrial Internet of Things is an important part, and there is a need to conserve spectrum as well as energy when communicating data to a fog or cloud back-end system. In this paper we investigate the benefits of fog computing by proposing a novel distributed learning model on the sensor device and simulating the data stream in the fog, instead of transmitting all raw sensor values to the cloud back-end. To save energy and to communicate as few packets as possible, the updated parameters of the learned model at the sensor device are communicated in longer time intervals to a fog computing system. The proposed framework is implemented and tested in a real world testbed in order to make quantitative measurements and evaluate the system. Our results show that the proposed model can achieve a 98% decrease in the number of packets sent over the wireless link, and the fog node can still simulate the data stream with an acceptable accuracy of 97%. We also observe an end-to-end delay of 180 ms in our proposed three-layer framework. Hence, the framework shows that a combination of fog and cloud computing with a distributed data modeling at the sensor device for wireless sensor networks can be beneficial for Industrial Internet of Things applications.

Overlay Enhanced Mobility for the Internet of Things

One of the major challenges to realize the Internet of Things is to support IP mobility for the large amount of connected entities when they move between different locations and access methods. Current solutions for mobility are host centric, requiring support from the infrastructure, or breaks backwards compatibility, which will take a long time or high economic motivation to implement. Solutions for context information exchange are created for specific, small, or localized scenarios with centralized coordination that do not scale well. There is therefore a need for a solution which both scales well, and support IP mobility, without additional demands on current or future Internet infrastructure.We propose the use of a dual-overlay network structure for both information dissemination and as an alternative to current IP mobility technologies. It separates identities from location by introducing a second overlay network where the identity-to-location association is stored. We show analytically that the proposed solution provide logarithmic latency for localization and reduces the overall workload when the number of sensors per host increases beyond seven, with a workload reduction of 15 percentage points at fifteen sensors per host.

Hybrid MAC mechanism for energy efficient communication in IEEE 802.11ah

Many applications for machine-to-machine (M2M) communications are characterized by large numbers of devices with sporadic transmissions and subjected to low energy budgets. This work addresses the importance of energy consumption by proposing a new Medium Access Control (MAC) mechanism for improving the energy efficiency of IEEE 802.11ah, a standard targeting M2M communication. We propose to use the features of IEEE 802.11ah MAC to realize a hybrid contention-reservation mechanism for the transmission of uplink traffic. In the proposed mechanism, any device with a buffered packet will first notify the Access Point (AP) during a contention phase before being given a reserved timeslot for the data transmission. We develop a mathematical model to analyse the energy consumption of the proposed mechanism and of IEEE 802.11ah. The results show that for a monitoring scenario, the proposed contentionreservation mechanism reduces the energy consumption for a successful uplink data transmission by up to 55%.

Gradual tune-in pictures for fast channel change

This paper presents a novel approach for fast channel change based on tune-in streams. The presented solution is based on gradual decoder refresh (GDR) with H.264 for the main and for the tune-in stream. In normal GDR mode a receiver would have to wait for several received NAL units of multiple frames before it can render a complete frame without visible GDR artifacts. We propose an additional tune-in stream that fills the missing regions of a partially complete frame. Our simulation results show that the solution is at least as bitrate-efficient as previous tune-in solutions but offers the advantages of a bitstream with less variable bitrate and a consistent gradual improvement of picture quality.