CAVLC, which stands for Context Adaptive Variable Length Coding, is an entropy coding method used in the H.264/AVC (Advanced Video Coding) video compression standard. Entropy coding is the process of representing data in a way that reduces its size by considering the probability of occurrence of different data elements. In simpler terms, it’s about representing frequently occurring elements with shorter codes and less frequent elements with longer codes. Here’s a brief overview of CAVLC:
Adaptiveness: What makes CAVLC “adaptive” is its ability to adjust its coding strategy based on the surrounding context. In this case, the context refers to the characteristics of the neighboring blocks of coefficients.
Application in H.264/AVC: CAVLC is primarily used in the Baseline profile of the H.264/AVC standard. This profile is tailored for low-complexity applications and scenarios where computational resources might be limited, such as video conferencing or mobile video.
Operation:
- CAVLC encodes the transform coefficients (which are obtained after transforming the spatial/temporal data into the frequency domain using the DCT-like transform) of a block.
- The process involves several steps, including:
- Level coding, which represents the magnitude of the coefficients.
- Run-length coding, which indicates consecutive zero coefficients.
- Finally, the coded level and run symbols are represented using variable length codes.
- The actual VLC (Variable Length Coding) tables used can vary based on the context, hence the “context-adaptive” part of the name.
Compared to CABAC: H.264/AVC also features another, more advanced entropy coding method called CABAC (Context Adaptive Binary Arithmetic Coding). CABAC is generally more efficient than CAVLC but is also more computationally intensive. As a result, CABAC is typically used in profiles of H.264/AVC that are designed for higher quality and more computational power, like the Main and High profiles.
In summary, CAVLC is a context-aware entropy coding method used in the H.264/AVC video compression standard. Its design balances efficiency and computational complexity, making it suitable for certain applications where resources might be constrained.