Subjective assessment of visual fidelity: Comparison of forced‐choice methods
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
Abstract Increases in display resolution, frame rate, and bit depth, particularly with advances in stereoscopic 3D (S3D) displays, have increased demand for efficient compression throughout the imaging pipeline. To meet such requirements, typically the aim is to reduce bandwidth while presenting content that is visually indistinguishable from the original uncompressed versions. Subjective image quality assessment is essential and multiple methods have been proposed. Of these, the ISO/IEC 29170‐2 flicker paradigm is a rigorous method used to define visually lossless performance. However, it is possible that the enhanced sensitivity to artifacts in the presence of flicker does not predict visibility under natural viewing conditions. Here, we test this prediction using high‐dynamic range S3D images and video under flicker and non‐flicker protocols. As hypothesized, sensitivity to artifacts was greater when using the flicker paradigm, but no differences were observed between the non‐flicker paradigms. Results were modeled using the Pyramid of Visibility, which predicted artifact detection driven by moderately low spatial frequencies. Overall, our results confirm the flicker paradigm is a conservative estimate of visually lossless behavior; it is highly unlikely to miss artifacts that would be visible under normal viewing. Conversely, artifacts identified by the flicker protocol may not be problematic in practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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