一种基于特征参数的SAR原始数据压缩方法
By performing feature parameter analysis and classification compression on SAR data blocks, and utilizing BAQ, DPCM, and Llyod-Max quantizers as well as information hiding methods, the problem of insufficient compression performance of raw SAR data was solved, achieving a more efficient data compression effect.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- XIAN INSTITUE OF SPACE RADIO TECH
- Filing Date
- 2023-09-26
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies struggle to effectively compress raw SAR data, especially on non-Gaussian distributed data blocks where compression performance is insufficient. Furthermore, traditional methods cannot adapt to complex imaging scenarios, leading to data rates exceeding downlink or storage space limitations.
By analyzing the feature parameters of the original SAR data blocks, it is determined whether they conform to a Gaussian distribution. The BAQ algorithm is used to compress data blocks that satisfy the Gaussian distribution, while the DPCM and Llyod-Max quantizers are used to compress data blocks that do not conform to the Gaussian distribution. Data blocks with large variances are replaced with the mean, and the difference is embedded in the compressed bitstream. Combined with information hiding methods, data classification and compression are achieved.
It improves the compression performance of SAR data, enhances the compression effect of non-Gaussian distributed data blocks, improves the overall compression ratio and quality, and adapts to the SAR data compression needs of different scenarios.
Smart Images
Figure CN117439613B_ABST