Huawei technologies co., ltd. (20240340425). Gaussian Mixture Model Entropy Coding simplified abstract
Contents
Gaussian Mixture Model Entropy Coding
Organization Name
Inventor(s)
Mikhail Vyacheslavovich Sosulnikov of Munich (DE)
Sergey Yurievich Ikonin of Moscow (RU)
Elena Alexandrovna Alshina of Munich (DE)
Gaussian Mixture Model Entropy Coding - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240340425 titled 'Gaussian Mixture Model Entropy Coding
The present disclosure describes a method for decoding an encoded signal that has been entropy encoded with one or more Gaussian Mixture Models (GMMs).
- Receiving at least one bitstream containing the encoded signal and information for obtaining parameters of the GMMs.
- Obtaining the GMM parameters based on the information from the bitstream.
- Entropy decoding the signal using the GMMs with the obtained parameters.
This innovation allows for efficient decoding of signals encoded with GMMs, improving data transmission and processing.
Potential Applications: - Data compression and transmission systems - Audio and video encoding and decoding - Image processing and recognition technologies
Problems Solved: - Efficient decoding of signals encoded with GMMs - Improved data compression and transmission efficiency
Benefits: - Enhanced data processing speed - Reduced bandwidth usage - Improved signal quality and accuracy
Commercial Applications: Title: Efficient Signal Decoding Technology for Data Transmission Systems This technology can be applied in telecommunications, multimedia systems, and data storage industries to enhance data processing and transmission efficiency.
Questions about Signal Decoding Technology: 1. How does this technology improve data compression efficiency? - This technology improves data compression efficiency by utilizing Gaussian Mixture Models for entropy encoding and decoding, reducing the amount of data needed for transmission.
2. What are the potential drawbacks of using Gaussian Mixture Models for signal decoding? - While GMMs can improve efficiency, they may require more computational resources for decoding, which could impact real-time processing in some applications.
Original Abstract Submitted
the present disclosure provides a method of decoding an encoded signal. the method includes receiving at least one bitstream comprising an encoded signal, the signal being entropy encoded with one or more gaussian mixture models (gmms), and the at least one bitstream comprising information for obtaining parameters of the one or more gmms. the method further includes obtaining the gmm parameters based on the information from the at least one bitstream; and entropy decoding the signal using the gmms with the obtained gmm parameters. the present disclosure further refers to a corresponding encoding method, decoder and encoder.
