Encoder Using Database Reference Matching for Data Compression
Solution Overview
Problem
Existing encoding methods for digital data, such as images and audio, face challenges in efficiently compressing and transmitting data due to increased size and complexity, requiring significant computational resources and bandwidth, while maintaining quality.
Innovation Solution
A method and system that encodes source data by matching data portions to database elements, recording reference values, and including these in the encoded data, allowing for efficient storage and transmission with improved quality and reduced data size, using static and dynamic databases for efficient data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional encoding methods are used to compress source data, then data size is reduced for transmission or storage, but decoded content quality deteriorates
Solution Approach 1:
The encoder performs preliminary actions by matching source data portions against database elements before encoding, recording reference values to database elements that match the source data. This preliminary matching allows the system to select optimal database elements that preserve quality while reducing data size, rather than applying generic compression algorithms that degrade quality.
Solution Approach 2:
A database serves as an intermediary between the source data and the encoded output. The database contains pre-processed elements that can be referenced instead of encoding the actual data portions, enabling lossless or high-quality compression while reducing the amount of data that needs to be transmitted or stored.
2Manufacturing precision
If encoding transforms are evolved and upgraded to improve quality, then decoded content quality is improved, but device complexity increases
Solution Approach 1:
Complex encoding transforms are performed in advance during database creation rather than during real-time encoding. The database stores results of sophisticated processing, allowing simple reference-based encoding at runtime. This separates the complex preprocessing stage from the simple encoding stage, reducing device complexity while maintaining quality.
Solution Approach 2:
Instead of implementing complex encoding transforms in every encoder device, the system creates a copy of processed data elements in a database. Encoders then simply reference these pre-processed copies, avoiding the need to implement complex transforms in each device while still benefiting from high-quality processing.
3Manufacturing precision
If more computational resources are allocated to encoding and decoding, then decoded content quality is improved, but bandwidth requirements increase
Solution Approach 1:
The database acts as an intermediary that enables efficient data representation. By referencing database elements instead of transmitting full encoded data, the system reduces bandwidth requirements while maintaining the ability to perform high-quality decoding using the pre-processed database elements.
Solution Approach 2:
The system extracts only the essential reference information from the source data that is needed to locate matching database elements. This extraction approach minimizes the amount of data that needs to be transmitted over bandwidth-constrained channels while preserving the ability to reconstruct high-quality decoded content at the destination.
Data Source
AI summary
A method of encoding source data to generate corresponding encoded data for transmission or storage includes matching one or more portions of the source data to one or more elements in one or more databases, wherein the one or more elements are representative of corresponding one or more data blocks, and recording reference values which relate the one or more portions of the source data to the one or more matched elements; and including the reference values in the encoded data together with the one or more databases and/or information identifying the one or more databases. The methods are implemented in an encoder, a decoder and in a codec. In the codec, the at least one encoder and the at least one decoder share one or more databases referred to by reference values included in the encoded data.