UNIVERSITY OF CALGARY Quality Assessment of Ikonos and Quickbird Fused Images
Bibliographic record
Abstract
New series of very high spatial resolution (VHR) satellites Ikonos and Quickbird have enabled mapping and updating of GIS databases of urban areas that is presently carried out using field surveys and aerial images. Satellites provide higher spatial resolution in panchromatic (PAN) mode compared to that in multispectral (MS) mode. High spatial and high spectral resolution are desirable for urban mapping as high spatial resolution provides better geometric quality while high spectral resolution provides better object identification. Image fusion techniques aim at increasing the spatial resolution of MS images using information from PAN image. However, fusion methods alter the spectral content of the original images. This is not desirable in applications requiring spectral information such as visual interpretation or classification procedures that depend on the spectral information of MS images. In this study, fused images obtained for Ikonos PAN and MS and Quickbird PAN and MS images by the standard methods namely IHS (Intensity-Hue-Saturation) and PCA (Principal Component Analysis), and simple wavelet methods namely, IHS with wavelet (IHS+W), PCA with wavelet (PCA+W), Wavelet
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".