Naslov
Mtltispectral Image Enhancement with extended Offset-sparsity Decomposition

Autori
Tian, Long ; Du, Qian ; Younan, Nicolas ; Kopriva, Ivica

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Geoscience and Remote Sensing Symposium (IGARSS), 2016 IEEE International / Wu, Ji ; Yin, Yaqiu - Piscataway (NJ) : Institute of Electrical and Electronics Engineers (IEEE), 2016, 4383-4386

ISBN
978-1-5090-3332-4

Skup
Geoscience and Remote Sensing Symposium (IGARSS), 2016 IEEE International

Mjesto i datum
Peking, Kina, 10.07.2016. - 15.07.2016

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
principle component analysis (PCA) ; offset-sparsity decomposition (OSD) ; Pseudo-I channel ; Multispectral image ; quality measurement

Sažetak
In this paper, the extended offset-sparsity decomposition methods are applied to multispectral image for enhancement, which contain principle component analysis of offset-sparsity decomposition (PCA-OSD) method and pseudo-I channel offset-sparsity decomposition method. The PCA and pseudo-I channel method could reduce the negative impact on of enhancement in the spectral domain. On the other hand, OSD enhances the image by increasing the sparsity, which leads to lower entropy with more data information. The extended sharpness and contrast quality measurements are applied for multispectral images. The experimental results demonstrate that extended OSD offers better performance of enhancement with acceptable spectral affection.

Izvorni jezik
Engleski

Znanstvena područja
Matematika, Računarstvo

Napomena
Rad je rezultat neformalne znanstvene suradnje Ivice Kopriva sa Instituta Ruđer Bošković i profesorice Qian Du, Mississippi State University, SAD.

POVEZANOST RADA