Pregled bibliografske jedinice broj: 1262827
Novel Block Sorting and Symbol Prediction Algorithm for PDE-Based Lossless Image Compression: A Comparative Study with JPEG and JPEG 2000
Novel Block Sorting and Symbol Prediction Algorithm for PDE-Based Lossless Image Compression: A Comparative Study with JPEG and JPEG 2000 // Applied sciences (Basel), 13 (2023), 5; 3152, 34 doi:10.3390/app13053152 (međunarodna recenzija, članak, znanstveni)
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Naslov
Novel Block Sorting and Symbol Prediction
Algorithm for PDE-Based Lossless Image
Compression:
A Comparative Study with JPEG and JPEG 2000
(Novel Block Sorting and Symbol Prediction
Algorithm for PDE-Based Lossless Image
Compression: A Comparative Study with JPEG and
JPEG 2000)
Autori
Livada, Časlav ; Horvat, Tomislav ; Baumgartner, Alfonzo
Izvornik
Applied sciences (Basel) (2076-3417) 13
(2023), 5;
3152, 34
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
block sorting ; compression ; objective and subjective quality assessment ; partial differential equations ; symbol prediction
Sažetak
In this paper, we present a novel compression method based on partial differential equations complemented by block sorting and symbol prediction. Block sorting is performed using the Burrows–Wheeler transform, while symbol prediction is performed using the context mixing method. With these transformations, the range coder is used as a lossless compression method. The objective and subjective quality evaluation of the reconstructed image illustrates the efficiency of this new compression method and is compared with the current standards, JPEG and JPEG 2000.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek,
Sveučilište Sjever, Koprivnica
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- Social Science Citation Index (SSCI)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus