Abstract

This work considers the design and practical implementation of JSCC-Cast, a comprehensive analog video encoding and transmission system requiring a reduced amount of digital metadata. Suitable applications for JSCC-Cast are multicast transmissions over time-varying channels and Internet of Things wireless connectivity of end devices having severe constraints on their computational capabilities. The proposed system exhibits a similar image quality compared to existing analog and hybrid encoding alternatives such as Softcast. Its design is based on the use of linear transforms that exploit the spatial and temporal redundancy and the analog encoding of the transformed coefficients with different protection levels depending on their relevance. JSCC-Cast is compared to Softcast, which is considered the benchmark for analog and hybrid video coding, and with an all-digital H.265-based encoder. The results show that, depending on the scenario and considering image quality metrics such as the structural similarity index measure, the peak signal-to-noise ratio, and the perceived quality of the video, JSCC-Cast exhibits a performance close to that of Softcast but with less metadata and not requiring a feedback channel in order to track channel variations. Moreover, in some circumstances, the JSCC-Cast obtains a perceived quality for the frames comparable to those displayed by the digital one.

Highlights

  • We present the results obtained from different computer experiments carried out in order to evaluate the performance of joint source channel coding (JSCC)-Cast

  • The design philosophy of the H.265 is significantly different than that of JSCC-Cast because JSCC-Cast aims at providing an acceptable video quality for a wide range of situations requiring a negligible amount of critical metadata, whereas the all-digital system focuses on providing as much quality as possible for a particular bandwidth ratio, which needs to be adapted depending on the channel conditions

  • In this work we have proposed JSCC-Cast, an analog video encoding and transmission system that is competitive with similar contemporary hybrid systems such as Softcast and even surpassing them under certain circumstances

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Summary

Introduction

Video system research and developmental studies are currently focused on digital systems due to their great adaptability, there are a number of situations in which analog encoding and transmission video systems can outperform their all-digital equivalents:. All-digital video systems require either certain channel information provided by a feedback channel or the transmission of a large amount of redundancy in order to ensure successful reception regardless of the channel conditions. All-digital video systems guarantee error-free transmissions above a certain channel quality, keeping fixed the received video quality, wasting bandwidth due to redundancy. Analog encoding and transmission video systems are simpler than their all-digital equivalents since the transmission is the same for all receivers, and no feedback channel is required. In order to address this objective, JSCC-Cast is proposed, which is a low-complexity scheme for encoding analog video with negligible digital metadata and with special emphasis on its suitability for Internet of things (IoT) systems. JSCC-Cast, a comprehensive analog video encoding and transmission system, is proposed which requires a minimum amount of metadata to reconstruct the video. This analysis allows us to evaluate the impact of several design parameters on the system performance and the quality of the resulting decoded video

All-Digital Video Systems
Hybrid Video Systems
Wavelet-Based Hybrid Systems
JSCC-Cast
AWGN Channel
Evaluation Metrics
Domain Transforms for Images and Video
Block Spatial Division of the Video Frames
Temporal Redundancy
Frequency Coefficients Rearrangement Pattern
Isoplane
Hyperboloid
Analysis of the Rearranging Methods
Redundancy Analysis
Evaluation and Results
Digital Implementation
Evaluation Based on SSIM and PSNR
Perceptual Evaluation Based on Visual Comparison
Metadata Evaluation
Conclusions
Future Work
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