Abrir el documento
|
Información general |
| Autor |
Camargo, Aldo; He, Qiang; Palaniappan, Kannappan |
| Publicado |
InTech Open Access Publisher, 2013
|
| Edición |
|
| Extensión |
|
| ISBN |
|
| Abstract |
Unmanned Aircraft Systems (UAS) have been
widely applied for reconnaissance and surveillance by
exploiting information collected from the digital
imaging payload. The super‐resolution (SR) mosaicing
of low‐resolution (LR) UAS surveillance video frames
has become a critical requirement for UAS video
processing and is important for further effective image
understanding. In this paper we develop a novel
super‐resolution framework, which does not require
the construction of sparse matrices. The proposed
method implements image operations in the spatial
domain and applies an iterated back‐projection to
construct super‐resolution mosaics from the
overlapping UAS surveillance video frames. The
Steepest Descent method, the Conjugate Gradient
method and the Levenberg‐Marquardt algorithm are
used to numerically solve the nonlinear optimization
problem for estimating a super‐resolution mosaic. A
quantitative performance comparison in terms of
computation time and visual quality of the superresolution
mosaics through the three numerical
techniques is presented. |
|
| |
|
International Journal of Advanced Robotic Systems
Autor: Ottaviano, Erika; Ceccarelli, Marco; Husty, Manfred; Yu, Sung-Hoon; Kim, Yong-Tae; Park, Chang-Woo; Hyun, Chang-Ho; Chen, Xiulong; Feng, Weiming; Sun, Xianyang; Gao, Qing; Grigorescu, Sorin M.; Pozna, Claudiu; Liu, Wanli; Zhankui, Wang; Guo, Meng; Fu, Guoyu; Zhang, Jin; Chen, Wenyuan; Peng, Fengchao; Yang, Pei; Chen, Chunlin; Ding, Rui; Yu, Junzhi; Yang, Qinghai; Tan, Min; Polden, Joseph; Pan, [...]
Publicado: 2004
|
|
Newsletter
DMG-Lib
Europeana
PDF
Univ. Cassino
