Increasing heterogeneity of networks and diversity of user capabilities have determined and sustained a strong interest in robust coding of visual content and flexible adaptation of the bitstreams to network and user conditions. As a result, several methods for robust coding and transmission have been proposed that include multiple description coding, motioncompensated subband video coding, joint source-channel coding, integrated compression and error control, and adaptation/transcoding solutions. These typically increase transmission robustness and network and user awareness by using scalability, error resilience, and adaptivity at little or sometimes no extra cost in coding efficiency. However, the performance of these methods is affected by the diversity of, and complex interactions within, the visual content. Analysis methods can improve the performance of robust methods for coding and transmission by providing solutions to account for vastly different characteristics of the visual content and complex interactions among data components, to achieve optimal or near-optimal robust solutions. Among several benefits, the application of visual analysis methods within robust coding and transmission frameworks such as those mentioned earlier yields content-aware error resilient solutions and improves prioritization of the visual content for coding and transmission. This special issue focuses on the seamless integration of visual analysis methods in, or joint design with, robust compression and transmission solutions. The special issue consists of three sections that address robust video coding architectures and configurations, robust entropy coding methods, and quality issues related to robust coding, respectively:
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