Lossy compression schemes can be based on a source model, as in the case of speech compression, or a user or sink model, as is somewhat the case in image compression. In this chapter we look at audio ...

This project presents a hybrid lossless compression system that combines an LSTM-based Recurrent Neural Network (RNN) with Arithmetic Coding. Traditional algorithms like Shannon–Fano use static ...

The Layer II coder provides a higher compression rate by making some relatively minor modifications to the Layer I coding scheme. These modifications include how the samples are grouped together, the ...

Coding, information theory and compression constitute the backbone of modern digital communications and data storage. Grounded in Shannon’s seminal work, information theory quantifies the ...

Abstract: We propose content compression coding for massive users, where correlated contents of grouped users can be utilized to achieve high compression efficiency. We divide the users into several ...

Artificial intelligence (AI) can be successfully applied to images and videos to improve how they look - to add colour, to understand their content better or to help with storytelling, for instance.

We are currently researching a video and audio coding technologies for advanced terrestrial broadcasting. Here, we present a real-time versatile video coding (VVC *) decoder that supports multilayer ...

Finding efficient ways to compress and decompress data is more important than ever. Compressed data takes up less space and requires less time and network bandwidth to transfer. In cloud service code, ...

Elegant drag-and-drop file upload interface Real-time compression with visual feedback Detailed compression statistics Download compressed files Implementation of the Huffman coding algorithm Huffman ...