Stateless Lossless Compression for Radiological Spectral Data
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Solution Overview
Problem
Current data compression methods for radiological gamma-ray spectral data are inefficient due to their stateful nature, requiring coordination between transmitter and receiver, and result in high transmission costs for sparse and invariant data from radiation sensors.
Innovation Solution
A stateless, lossless data encoding method that transforms radiation spectra into a serialized bit-plane representation, using bit-plane rearrangement and variable-length encoding techniques like unary and Golomb encoding to reduce data dimensionality and encode differences between set bits, eliminating the need for maintaining state between transmitter and receiver.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If stateful compression algorithms are used for radiation spectral data, then compression performance is improved, but device complexity and coordination requirements increase
Solution Approach 1:
The patent segments the radiation spectral data into multiple bit-planes based on bit significance (LSB to MSB). Each bit-plane is processed independently through run-length encoding, eliminating the need for complex stateful coordination while achieving efficient compression of the original data stream
Solution Approach 2:
The patent transforms the one-dimensional spectral data stream into a multi-dimensional bit-plane structure. By organizing data across multiple bit-significance dimensions and processing each dimension independently, the system achieves compression without requiring stateful coordination between transmitter and receiver
2Loss of information
If all radiation sensor data is transmitted and archived, then data completeness is improved, but transmission costs increase
Solution Approach 1:
The patent extracts and transmits only the essential compression metadata (bit-plane structure, run-length encoded values, encoding parameters) rather than the complete raw data. This extraction approach maintains data completeness for lossless reconstruction while dramatically reducing transmission volume and associated costs
3Productivity
If bit-plane rearrangement is applied to histogram data, then compression efficiency is improved, but processing complexity increases
Solution Approach 1:
The patent segments the histogram data into distinct bit-planes based on bit significance. This segmentation transforms a complex compression problem into multiple simpler, independent run-length encoding operations, improving compression efficiency while keeping each processing step relatively simple
Solution Approach 2:
The patent changes the representation parameter of the data from raw histogram values to bit-plane organized binary representations. This parameter transformation enables more effective run-length encoding by grouping identical bit values across multiple data points, thereby improving compression efficiency
Data Source
AI summary
An approach for gathering, encoding and transmitting histogram data mitigates the need for transmission resources by compressing the gathered data in a lossless, stateless manner for transmission. A generally sparse data set benefits from an encoding mechanism based on a bit plane arrangement of the raw data. The approach organizes bit planes in a sequential manner, and then encodes values based on intervals of non-zero bit positions. By traversing a sequential string based on the bit plane, each “run” of zeroes tends to produce relatively small values, easing encoding burdens, but also accommodated larger values when necessary. A selective encoding technique invokes different encoding processes based on the magnitude of the interval, to allow use of an encoding that stores each respective value in the fewest bits. Different encoding techniques are applied based on ranges of the interval magnitude, or zero run.