Enhancing Spatial Resolution of Hyperspectral Imagery Using Sensor's Intrinsic Keystone Distortion
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Bibliographic record
Abstract
In this paper, we develop a novel technology that can enhance the spatial resolution of hyperspectral data cube without using any additional images, as would be the case in image fusion. The technology exploits interband spatial misregistration or distortion (often referred to as “keystone”) of the sensor that acquired the data cube and uses it as additional information to increase the spatial resolution of the data cube. Three methods have been developed to derive subpixel-shifted images from the data cube itself in exploiting the sensor's intrinsic characteristics. Two schemes were proposed to organize the derived subpixel-shifted images before being integrated into the high-resolution image using the iterative-back-projection fusion. Experimental results show that the technology can enhance the spatial resolution in the cross-track direction of hyperspectral data cubes by a factor of two.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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