Imaging Signal Compression via Decorrelation and Wavelet Decomposition
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Solution Overview
Problem
High data throughput from multiple transducers in imaging devices, such as ultrasound and radar systems, leads to signal interference and loss during transmission, particularly due to increased complexity and changing operating parameters, necessitating an efficient compression and decompression scheme to accommodate these challenges.
Innovation Solution
A system and method that compresses imaging data using decorrelation, wavelet decomposition, and quantization operations to generate a compressed bit stream, which is then decompressed upon reception, allowing for adjustable compression levels to minimize interference and loss during transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of transducers and sampling frequency are increased to improve imaging quality, then the data throughput increases, but signal interference and loss during transmission worsen
Solution Approach 1:
The patent extracts only the essential imaging information from the high-volume transducer data through compression algorithms, separating critical signal components from redundant data before transmission. This reduces the data volume requiring transmission while preserving the core imaging quality, thereby mitigating signal interference and loss during cable transmission.
Solution Approach 2:
The system dynamically adjusts transmission parameters including compression level, data format, and sampling rate based on cable length and operating conditions. By changing these parameters adaptively, the system maintains optimal balance between imaging quality and transmission reliability under varying operational scenarios.
2Manufacturing precision
If the data throughput is increased to maintain high sampling resolution, then the imaging detail is improved, but the risk of signal interference and loss increases
Solution Approach 1:
The patent applies compression and data optimization processing before the transmission stage, preliminarily preparing the data in a format that is more resistant to interference. By pre-processing the high-resolution data to extract essential features and reduce redundancy, the system protects against signal interference during transmission while maintaining the ability to reconstruct high-resolution images.
3Adaptability or versatility
If the cable length is increased to accommodate device architecture, then the component placement flexibility is improved, but the signal loss during transmission worsens
Solution Approach 1:
The system extracts and transmits only the essential imaging data through the cable rather than raw high-volume signals. This extraction of critical information reduces the energy and signal strength requirements for transmission, allowing longer cable lengths without excessive signal loss while maintaining architectural flexibility.
4Productivity
If the compression level is increased to reduce data volume, then the transmission efficiency is improved, but the complexity of the compression scheme increases
Solution Approach 1:
The patent implements a dynamic compression system that adjusts the compression level and algorithm selection based on real-time operating conditions, cable length, and imaging requirements. This dynamic adaptation allows the system to optimize transmission efficiency for each scenario without requiring a permanently complex compression scheme, as the complexity is only activated when needed.
Data Source
AI summary
An imaging device is provided, comprising: a decorrelation circuit configured to receive K initial imaging signals and to perform a decorrelation operation on K initial imaging signals, respectively, to generate K decorrelated imaging signals; Kh wavelet decomposition circuits configured to perform K wavelet decomposition operations on the K decorrelated imaging signals, respectively, to generate K decomposed imaging signals; K quantization circuits configured to perform K quantization operations on the K decomposed imaging signals, respectively, to generate K quantized imaging signals; and a bit multiplexer configured to generate a compressed bit stream based on the K quantized imaging signals; a data line configured to pass the compressed bit stream; and a decompressor module configured to convert the compressed bit stream into K recovered imaging signals corresponding to the K initial imaging signals, wherein K is an integer greater than 1.