Residual Data Compression Using Dual Lossy Encoding
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Solution Overview
Problem
Existing data compression techniques often result in suboptimal compression rates when a single method is applied to diverse data sets, leading to inefficiencies in storage and transfer, particularly for large-scale data generated by IoT devices.
Innovation Solution
A data compression system that employs multiple lossy compression methods, selectively applying each technique to different parts of the data to optimize the compression rate, using processors and storage devices to generate and manage compressed data with residual information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single lossy compression method is used for all data, then the device complexity is reduced, but the compression rate becomes suboptimal for diverse data types
Solution Approach 1:
The patent divides the compression process into multiple stages, applying different compression methods (first lossy compression method and second lossy compression method) to different portions or representations of the data. This segmentation allows each compression method to be optimized for specific data characteristics, thereby improving overall compression rate without requiring a single overly complex system to handle all data types uniformly
Solution Approach 2:
The patent applies different compression techniques to different parts of the data based on local characteristics. By using a first lossy compression method for certain data portions and a second lossy compression method for others, the system tailors the compression approach to the specific properties of each data segment, achieving optimal compression rates for diverse data types while maintaining manageable system complexity
2Productivity
If multiple lossy compression methods are applied to different data parts, then the compression rate is improved, but the processing time and computational resources increase
Solution Approach 1:
The patent applies a first lossy compression method as a preliminary compression step before applying a second lossy compression method. This preliminary action reduces the data size and complexity early in the process, making the subsequent compression step more efficient. By performing preliminary compression, the system achieves better overall compression rates while managing processing time through staged rather than simultaneous multi-method application
Data Source
AI summary
A data compression system compresses original data by a first lossy compression method to generate first compressed data, decompresses the first compressed data to generate first decompressed data, extracts residual information between the original data and the first decompressed data, compresses the residual information by a second lossy compression method different from the first lossy compression method to generate second compressed data, and stores the first compressed data and the second compressed data in the one or more storage devices.