Adoption of New Image and Video Coding Standards standard is currently the H.264/MPEG-4 Advanced video coding (AVC) (Wiegand et al., 2003), which was initially developed between 1999 and 2003, and was then extended in 2003–2009. So far, most hardware manufacturers support it, such that it is still a fundamental video technology in a wide range of video applications, including almost all the major platforms for video streaming. After AVC, the other adopted standard is the High Efficiency Video Coding (HEVC) standard (Sullivan et al., 2012), that was finalized in 2013, providing about a 50% bit-rate reduction compared with AVC standard.
The efficiency of current video coding standards, like H.264 and HEVC, is still not sufficiently high for today's heterogeneous data-intensive multimedia applications, that often work in a wireless transmission environment or with limited computational resources. Thus, there is an ever-increasing request for Spain phone number list developing new video coding standards showing a high compression ratio and, at the same time, high visual quality (Zhang and Mao, 2019). This request can be alleviated by the fact that the available computational power keeps rising, thanks to the adoption of parallel computing together with hardware acceleration, thus allowing to adopt more complex and effective coding algorithms, even if still based on the principles of transform coding and predictive coding.
User interface designers should understand how the retrieval algorithms works so that specific interface features can be designed to take advantage of the algorithms, as well as to compensate for their weaknesses. An early example of integrated design is Qiu et al. (2007) where image features (colors) used in organizing the database images into clusters are directly reflected on the interface, and the indexing keys are used to partition the display areas such that the interface provides an intuitive “mental image” of the database. It is hoped that we will see more such integrated design in the future to advance state of the art in image and video retrieval.