Applications of wavelet data compression using modified zerotrees in remotely sensed data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A computationally simple and effective wavelet transform based data compression algorithm has been developed at the Canadian Space Agency. It uses modified zerotrees and an optimized multi-level lookup table to improve the performance of an embedded zerotree wavelet algorithm. This new algorithm is either comparable to or surpasses previous algorithms which are much more sophisticated and computationally complex. In this paper, this algorithm was applied to compression of remotely sensed data acquired by the Airborne Visible/Infrared imaging Spectrometer (AVIRIS) and the Compact Airborne Spectrographic Imager (CASI). In order to evaluate the performance of the algorithm, the compression results obtained by this algorithm were compared with those by the LuraWave, as well as by the JPEG. The experiments show that compression ratios over 32:1 can be achieved with the fidelities greater than 40.0 dB.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it