Primena modela predikcije praga uočljivih razlika u proceni kvaliteta slika sa JPEG kompresijom
Sažetak
Uvod/cilj: U radu su predstavljena interesantna istraživanja koja se odnose na analizu performansi modela predikcije praga uočljivih razlika (JND) na nivou slike i njegovu primenu u proceni kvaliteta slika sa JPEG kompresijom.
Metode: Analiza performansi JND modela sprovedena je na indirektan način kroz zanimljivu ideju da se koriste javno dostupne baze slika sa rezultatima subjektivnih testova, sa podelom slika na dve klase (iznad i ispod praga uočljivih razlika). U analizi performansi predikcije JND modela i pri proceni kvaliteta korišćeno je pet baza slika, od kojih četiri potiču iz vidljivog opsega talasnih dužina, dok je jedna baza sa slikama iz infracrvenog dela elektromagnetnog spektra namenjenih daljinskom osmatranju i nadzoru.
Rezultati: U radu je pokazano da se primenom JND modela sa većom preciznošću mogu estimirati subjektivni skorovi kvaliteta, što vodi značajnom poboljšanju performansi tradicionalnog vršnog odnosa signal/šum (PSNR). Dobitak ostvaren uvođenjem JND modela na nivou slike u objektivnu procenu zavisi od izabrane baze i rezultata polazne jednostavne PSNR mere, a ostvaren je na svih pet baza. Srednja vrednost koeficijenta linearne korelacije (za pet baza) između subjektivnih i PSNR objektivnih estimacija kvaliteta je sa 74% (tradicionalni PSNR) porasla na 90% (PSNR sa JND modelom na nivou slike).
Zaključak: Dodatno unapređenje JND zasnovane objektivne mere može se dobiti unapređenjem modela predikcije JND.
Reference
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