TY - GEN
T1 - Resolution enhancement algorithm based on wavelet and edge extraction techniques in noise presence
AU - Chavez-Roman, O. H.
AU - Ponomaryov, V.
AU - Loboda, I.
PY - 2013
Y1 - 2013
N2 - The images and video sequences registering in optical, radar, medical applications, presented in digital photographs, on HD TV, in electron microscopy, etc. are obtained from electronic devices that use different sensors [1-3]. The visual quality of the images and frames in the video sequences depend on spatial resolution, and because of the physical limitations this suffers of precision needed that can be improved developing better sensors via manufacturing process that seems as a difficult and high cost task. That is why, in many applications of the image/video processing, the additional methods and algorithms are developed where the goal is to restore the resolution degraded in a sensor, permitting better observations of the fine details, edges, etc. [1, 4, 5]. This can be performed using the super resolution (SR) procedures generating a high-resolution (HR) images from one or several low-resolution (LR) images/video frames [1-6]. The goal of the developed algorithm is to provide better resolution than those obtained by other state-of-the-art filter. A number of approaches have been proposed designing the SR algorithms [1-7]. Among them there are: the nearest neighbor algorithms, the bilinear interpolation, the bi-cubic technique, the fuzzy logic methods and techniques based on the spline technique. Image resolution enhancement using wavelet transform (WT) domain is a relatively new subject, and recently many novel algorithms have been designed [6-9].
AB - The images and video sequences registering in optical, radar, medical applications, presented in digital photographs, on HD TV, in electron microscopy, etc. are obtained from electronic devices that use different sensors [1-3]. The visual quality of the images and frames in the video sequences depend on spatial resolution, and because of the physical limitations this suffers of precision needed that can be improved developing better sensors via manufacturing process that seems as a difficult and high cost task. That is why, in many applications of the image/video processing, the additional methods and algorithms are developed where the goal is to restore the resolution degraded in a sensor, permitting better observations of the fine details, edges, etc. [1, 4, 5]. This can be performed using the super resolution (SR) procedures generating a high-resolution (HR) images from one or several low-resolution (LR) images/video frames [1-6]. The goal of the developed algorithm is to provide better resolution than those obtained by other state-of-the-art filter. A number of approaches have been proposed designing the SR algorithms [1-7]. Among them there are: the nearest neighbor algorithms, the bilinear interpolation, the bi-cubic technique, the fuzzy logic methods and techniques based on the spline technique. Image resolution enhancement using wavelet transform (WT) domain is a relatively new subject, and recently many novel algorithms have been designed [6-9].
UR - http://www.scopus.com/inward/record.url?scp=84888599055&partnerID=8YFLogxK
U2 - 10.1109/MSMW.2013.6622152
DO - 10.1109/MSMW.2013.6622152
M3 - Contribución a la conferencia
AN - SCOPUS:84888599055
SN - 9781479910663
T3 - Proceedings - 2013 International Kharkov Symposium on Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves, MSMW 2013
SP - 593
EP - 595
BT - Proceedings - 2013 International Kharkov Symposium on Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves, MSMW 2013
T2 - 2013 International Kharkov Symposium on Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves, MSMW 2013
Y2 - 23 June 2013 through 28 June 2013
ER -