Variable-Block Data Compression for Low-Bandwidth Error Control

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Solution Overview

Problem

Existing data compression techniques face challenges in minimizing errors during compression and decompression, especially when dealing with large data sets transmitted over low bandwidth links like satellites, which require efficient compression methods to manage variable data and null values effectively.

Innovation Solution

The implementation of variable block size compression, efficient storage of null values, and methods to eliminate error growth in time series data, using techniques such as Discrete Cosine Transform (DCT) and quantization, along with dynamic block subdivision and error tolerance thresholds, to optimize compression while maintaining data accuracy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If data compression is applied to large data sets for transmission over low bandwidth links, then transmission efficiency is improved, but error in compression and decompression increases

Engineering Contradiction:

Improvetransmission efficiencyVSAvoiderror in compression and decompression

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The patent divides the data set into multiple blocks and applies different compression techniques to different blocks based on their characteristics. This segmentation allows the system to optimize for both compression efficiency and error minimization in different data regions, resolving the contradiction between transmission efficiency and reliability.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent dynamically adjusts compression parameters such as block size, quantization levels, and compression ratios based on data characteristics and error tolerance requirements. By changing these parameters adaptively, the system achieves high transmission efficiency while maintaining acceptable error levels.

Inventive Principle:

Principle #35Parameter changes

2Quantity of substance

If aggressive compression techniques are used to reduce data size, then bandwidth requirements are reduced, but data accuracy deteriorates

Engineering Contradiction:

Improvedata sizeVSAvoiddata accuracy

Core Design Contradiction:

Quantity of substanceVSMeasurement precision

Solution Approach 1:

The patent applies different compression aggressiveness levels to different data blocks based on their local characteristics. Critical data regions use more conservative compression to preserve accuracy, while less critical regions use aggressive compression to reduce size, thus resolving the contradiction between data size reduction and accuracy maintenance.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent applies compression selectively rather than uniformly across all data. By applying aggressive compression only where acceptable and using lighter compression where needed, the system achieves overall size reduction while maintaining necessary accuracy levels.

Inventive Principle:

Principle #16Partial or excessive action

3Productivity

If variable block size compression is implemented to handle different data characteristics, then compression efficiency is improved, but system complexity increases

Engineering Contradiction:

Improvecompression efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent implements dynamic block size selection where the compression system adapts block dimensions based on data characteristics. This dynamic approach improves compression efficiency by matching block sizes to data patterns while using automated algorithms to manage the complexity of variable parameters.

Inventive Principle:

Principle #15Dynamics

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach reduces errors in data compression and decompression, enables efficient transmission of large data sets over low bandwidth links, and ensures accurate representation of scientific data with controlled loss, improving the overall performance of data processing and transmission.

Implementation Method 1

using techniques such as Discrete Cosine Transform (DCT) and quantization

Methodology Applied

Scientific EffectDiscrete Cosine Transform:

Implementation Method 2

using techniques such as Discrete Cosine Transform (DCT) and quantization

Methodology Applied

Scientific EffectQuantization:

Data Source

PatentUS11418213B2Reducing error in data compression

Publication Date: 2022.08.16 THE GOVERNMENT OF THE UNITED STATES OF AMERICA AS REPRESENTED BY THE SECRETARY DEPARTMENT OF HEALTH & HUMAN SERVICES

AI summary

Systems and methods are provided for reducing error in data compression and decompression when data is transmitted over low bandwidth communication links, such as satellite links. Embodiments of the present disclosure provide systems and methods for variable block size compression for gridded data, efficiently storing null values in gridded data, and eliminating growth of error in compressed time series data.