Abstract
Pictures are changed over into computerized information by changing over every one of the pixels in the picture. The more hues that are utilized, the more noteworthy the measure of information that is required to store the picture. Picture pressure is the way toward diminishing these number of bits required to speak to a picture. The mainstream picture pressure calculation is the vector quantization, which maps the pixel force vectors into twofold vectors ordering a predetermined number of potential multiplications. The picture is divided into numerous squares, and each square is considered as a vector. After quickly checking on the central thoughts of vector quantization, we present a technique for the codebook structure for vector quantization calculations that perform picture handling.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Gersho A, Gray RM (1991) Vector quantization and signal compression. Kluwer, Boston, MA
Linde Y, Buzo A, Gray RM (1980) An algorithm for vector quantizer design. IEEE Trans Commun COMM 28:84–95
Neal JBO (1976) Differential pulse with entropy coding. IEEE Trans Inf Theory IT 22:169–174
Kumar A, Sharma K, Dixit AR, A review of the mechanical and thermal properties of graphene and its hybrid polymer nanocomposites for structural applications. J Mater Sci 54(8):5992–6026
Sharma K, Shukla M (2014) Three-phase carbon fiber amine functionalized carbon nanotubes epoxy composite: processing, characterisation, and multiscale modeling. J Nanomater
Kohonen T (1988) Self-organization and associate memory, 2nd edn. Springer, Berlin, Germany
Sharma K, Kaushalyayan KS, Shukla M, Pull-out simulations of interfacial properties of amine functionalized multi-walled carbon nanotube epoxy composites. Comput Mater Sci 99:232–241
Yadav A, Kumar A, Singh PK, Sharma K, Glass transition temperature of functionalized graphene epoxy composites using molecular dynamics simulation. Integr Ferroelectr 186(1):106–114
Singh PK, Sharma K, Kumar A, Shukla M, Effects of functionalization on the mechanical properties of multiwalled carbon nanotubes: A molecular dynamics approach. J Compos Mater 51(5):671–680
Singh PK, Sharma K, Mechanical and viscoelastic properties of in-situ amine functionalized multiple layer graphene/epoxy nanocomposites. Curr Nanosci 14(3):252–262
Vaisey I, Gersho A, Image variable block size segmentation. IEEE Trans Signal Process ASSP 40:2040
Singh PK, Sharma K (2018) Molecular dynamics simulation of glass transition behaviour of polymer based nanocomposites. J Sci Ind Res 77(10):592–595
Kumar A, Sharma K, Dixit AR, Carbon nanotube-and graphene-reinforced multiphase polymeric composites: review on their properties and applications. J Mater Sci 1–43
Shukla MK, Sharma K, Effect of carbon nanofillers on the mechanical and interfacial properties of epoxy based nanocomposites: a review. Polym Sci Ser A 61(4):439–460
Kumar A, Sharma K, Dixit AR, A review on the mechanical and thermal properties of graphene and graphene-based polymer nanocomposites: understanding of modelling and MD simulation. Mol Simul 46(2):136–154
Mausam K, Sharma K, Bharadwaj G, Singh RP, Multi-objective optimization design of die-sinking electric discharge machine (EDM) machining parameter for CNT-reinforced carbon fibre nanocomposite using grey relational analysis. J Braz Soc Mech Sci Eng 41
Yang SB, Tseng LY (2001) Smooth slide classified vector quantizer with variable block size. IEEE Trans Image Process 685
Kumar K, Sharma K, Verma S, Upadhyay N, Experimental investigation of graphene-paraffin wax nanocomposites for thermal energy storage. Mater Today Proc 18:5158–5163
Goyal M (2018) Shape, size and phonon scattering effect on the thermal conductivity of nanostructures. Pramana 91(6):87
Ziv J, Lempel A (1977) A universal algorithm for sequential data compression. IIEEE Trans Inf Theory IT-23(3):337–343
Goyal M, Gupta B (2019) Study of shape, size and temperature-dependent elastic properties of nanomaterials. Mod Phys Lett B 33(26):1950310
Goyal M, Gupta B (2019) Analysis of shape, size and structure dependent thermodynamic properties of nanowires. High Temp High Pressures 48
Goyal M, Singh M (2020) Size and shape dependence of optical properties of nanostructures. Appl Phys A 126(3):1–8
Agarwal R, Jalal AS, Arya KV (2020) A review on presentation attack detection system for fake fingerprint. Mod Phys Lett B 34(05):2030001
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Agrawal, R., Mohan, N. (2022). Image Compression Using Vector Quantization. In: Gao, XZ., Tiwari, S., Trivedi, M.C., Singh, P.K., Mishra, K.K. (eds) Advances in Computational Intelligence and Communication Technology. Lecture Notes in Networks and Systems, vol 399. Springer, Singapore. https://doi.org/10.1007/978-981-16-9756-2_34
Download citation
DOI: https://doi.org/10.1007/978-981-16-9756-2_34
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-9755-5
Online ISBN: 978-981-16-9756-2
eBook Packages: EngineeringEngineering (R0)