A case study on entropy-aware block-based linear transforms for lossless image compression
Borut Žalik, David Podgorelec, Ivana Kolingerová, Damjan Strnad, Štefan Kohek · 2024
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Description
Shrinking photo files without losing a pixel of data is a quiet contest among algorithms. Borut Žalik, David Podgorelec, Ivana Kolingerová, Damjan Strnad, and Štefan Kohek enter it in a 2024 study. Their framework tunes transforms block by block.
Eleven methods run inside the frame, from predictors to string tricks. Thirty-two gray photos of mixed size and content serve as tests. The frame cut information clutter past two famed predictors. Side data for each block adds its own byte cost. Even with that cost, final files ran smaller. Block-wise tuning, they show, beats one global rule.
Catalog record
| CREATOR | Borut Žalik, David Podgorelec, Ivana Kolingerová, Damjan Strnad, Štefan Kohek |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 37 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |