This item is printed on demand - it takes 3-4 days longer - Neuware -Many effective approaches designed to solve ill-posed and ill-conditioned problem had deficiencies to fulfill the needs of point spread function (PSF), which is hard to get into the practical situation all the time. So this project introduces a method called as Sparse signal representation for a single-image Super Resolution. The research on image Statistics gives a forward step to represent the image patches in a better way, as a sparse linear combination of elements, which are chosen from complete dictionary. From the coefficients of the sparse representation are utilized to construct the high-resolution output image. Here it trains two dictionaries jointly for the low-and high-resolution image patch, which produces two individual dictionary and it shows that the sparse representations for low- and high-resolution is same. To produce a high resolution image patch, the sparse representation can put together two trained dictionaries of the low- and the high-resolution image patch. A large amount of image patch pair are sampled here, by decreasing the computational cost significantly. 52 pp. Englisch.

N� de ref. del art�culo 9786202803175

Contactar al vendedor

Denunciar este art�culo

Detalles bibliogr�ficos

T�tulo: Sparse Signal Representation for a single-image Super Resolution
Editor: LAP LAMBERT Academic Publishing Sep 2020
Fecha de publicaci�n: 2020
Idioma: Ingl�s
ISBN 10: 6202803177
ISBN 13: 9786202803175
Encuadernaci�n: Taschenbuch
Estado: Neu

Acerca de

Sinopsis

Many effective approaches designed to solve ill-posed and ill-conditioned problem had deficiencies to fulfill the needs of point spread function (PSF), which is hard to get into the practical situation all the time. So this project introduces a method called as Sparse signal representation for a single-image Super Resolution. The research on image Statistics gives a forward step to represent the image patches in a better way, as a sparse linear combination of elements, which are chosen from complete dictionary. From the coefficients of the sparse representation are utilized to construct the high-resolution output image. Here it trains two dictionaries jointly for the low-and high-resolution image patch, which produces two individual dictionary and it shows that the sparse representations for low- and high-resolution is same. To produce a high resolution image patch, the sparse representation can put together two trained dictionaries of the low- and the high-resolution image patch. A large amount of image patch pair are sampled here, by decreasing the computational cost significantly.

"Sobre este t�tulo" puede pertenecer a otra edici�n de este libro.

Descripci�n de la librer�a

Ver la p�gina web de la librer�a

Informaci�n empresarial del vendedor

BuchWeltWeit Ludwig Meier e.K.
Germany

Condiciones de venta y env�o

Condiciones de venta

???????????????????????????????????????????????????????
Allgemeine Gesch�ftsbedingungen mit Kundeninformationen
???????????????????????????????????????????????????????

Inhaltsverzeichnis
??????????????????