On Encryption Algorithm of Color Image Based on Single Channel RGB Components
Why this work is in the frame
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Bibliographic record
Abstract
In order to ensure the safety and reliability of image transmission,a novel encryption of color image algorithm based on single channel RGB components has been studies in this paper,to solve the problem which traditional multi-channel algorithms cannot synchronous encryption and large load.Firstly,RGB components of color image have been extracted,plural matrix obtained by the discrete cosine transform and ZigZag,and complex matrix scrambled by the logistic chaos;secondly,inverse discrete cosine transform and chaos masking have been used to reconstruction and encryption RGB component to obtain crypt image;finally,the performance has been tested by simulation experiments.The results show that,compared with other color image encryption algorithms,the proposed algorithm has some good characteristics such as good confusion and diffusion properties,decryption speed,can resist various attacks and can effectively guarantee the security of image encryption,so it has a certain practical value.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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