Title :
Numerical Reconstruction and Compression of Thermal Image Sequences
Author :
Rovid, Andras ; Szeidl, Laszlo ; Hashimoto, Toshikazu
Author_Institution :
John von Neumann Fac. of Infomatics, Obuda Univ., Budapest, Hungary
Abstract :
Data compression and enhancement represent an important consideration in many application areas. The transmission bandwidth and storage capacity are often crucial factors. The efficiency of the processing of data in numerous cases strongly depends on the form of data representation. In the present paper a method, based on the so called higher order singular value decomposition and tensor-product transformation, is introduced for multidimensional scaling and compression of thermal images sequences. The proposed approach operates with smooth functions forming an orthonormal basis. Because of the smoothness property of these orthonormal components, the method can advantageously be utilized for the efficient compression of thermal image sequences.
Keywords :
data compression; data structures; image coding; image enhancement; image reconstruction; image sequences; infrared imaging; singular value decomposition; tensors; data compression; data enhancement; data processing efficiency; data representation; higher order singular value decomposition; multidimensional scaling; numerical compression; numerical reconstruction; orthonormal basis; orthonormal components; smooth functions; storage capacity; tensor-product transformation; thermal image sequences; transmission bandwidth; compression; image sequence; reconstruction; thermal image;
Conference_Titel :
Emerging Trends in Engineering and Technology (ICETET), 2012 Fifth International Conference on
Conference_Location :
Himeji
Print_ISBN :
978-1-4799-0276-7
DOI :
10.1109/ICETET.2012.40