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VLSI Implementation & Analysis of Block Based Compression Algorithms - Couverture souple

Kumaran, Muthu

 
9783330652040: VLSI Implementation & Analysis of Block Based Compression Algorithms
Couverture souple
ISBN 10 : 3330652047 ISBN 13 : 9783330652040
Editeur : Scholars' Press, 2017

Synopsis

The VLSI Implementation and Analysis of Block Based Compression Algorithm is used to analyse the images within each pixel before the storage space processes and therefore the size of the memory gets reduced. Here, differential values are captured and quantized, then the differential coding scheme uses the concept of selecting the brightest pixel as the reference pixel. The difference between brightest pixel and successive pixel is calculated and quantized. Hence, their range is compressed and the spatial redundancy can be removed using BBC algorithm. Thus, the proposed scheme reduces the accumulation of error and also reduces the requirement of memory. Thus, the Peak Signal to Noise Ratio value can be improved and Bits per Pixel value can be reduced. This is created for any given input image and thus the input image may be of any form. After that the image is converted into the binary form or header file conversion and these files are implemented into Xilinx Platform Studio and analyzed.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

The VLSI Implementation and Analysis of Block Based Compression Algorithm is used to analyse the images within each pixel before the storage space processes and therefore the size of the memory gets reduced. Here, differential values are captured and quantized, then the differential coding scheme uses the concept of selecting the brightest pixel as the reference pixel. The difference between brightest pixel and successive pixel is calculated and quantized. Hence, their range is compressed and the spatial redundancy can be removed using BBC algorithm. Thus, the proposed scheme reduces the accumulation of error and also reduces the requirement of memory. Thus, the Peak Signal to Noise Ratio value can be improved and Bits per Pixel value can be reduced. This is created for any given input image and thus the input image may be of any form. After that the image is converted into the binary form or header file conversion and these files are implemented into Xilinx Platform Studio and analyzed.

Biographie de l'auteur

Dr. N. Muthukumaran was born in Kaniyakumari, Tamilnadu, India, in 1984. He received the B.E, M.E and Ph.D Degree from Anna University, Chennai, India. He is currently working as an Professor, Anna University Recognized as a Research Supervisor for guiding Ph.D, & Research centre lab, Francis Xavier Engineering College, Tamilnadu, India.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Scholars' Press
Date d'édition
2017
Langue
anglais
ISBN 10 
3330652047
ISBN 13 
9783330652040
Reliure
Broché
Nombre de pages
52
Coordonnées du fabricant
non disponible
Personne responsable
non disponible