Performance Augmentation of Cuckoo Search Optimization Technique Using Vector Quantization in Image Compression

Aditya Bakshi, Akhil Gupta, Sudeep Tanwar, Gulshan Sharma, Pitshou N. Bokoro, Fayez Alqahtani, Amr Tolba, Maria Simona Raboaca

Research output: Contribution to journalArticlepeer-review

Abstract

For constructing the best local codebook for image compression, there are many Vector Quantization (VQ) procedures, but the simplest VQ procedure is the Linde–Buzo–Gray (LBG) procedure. Techniques such as the Gaussian Dissemination Function (GDF) are used for the searching process in generating a global codebook for particle swarm optimization (PSO), Honeybee mating optimization (HBMO), and Firefly (FA) procedures. However, when particle velocity is very high, FA encounters a problem when brighter fireflies are trivial, and PSO suffers uncertainty in merging. A novel procedure, Cuckoo Search–Kekre Fast Codebook Generation (CS-KFCG), is proposed that enhances Cuckoo Search–Linde–Buzo–Gray (CS-LBG) codebook by implementing a Flight Dissemination Function (FDF), which produces more speed than other states of the art algorithms with appropriate mutation expectations for the overall codebook. Also, CS-KFGC has generated a high Peak Signal Noise Ratio (PSNR) in terms of high duration (time) and better acceptability rate.

Original languageEnglish
Article number2364
JournalMathematics
Volume11
Issue number10
DOIs
Publication statusPublished - May 2023

Keywords

  • codebook
  • encoding
  • image compression (Img Comp)
  • vector quantization (VQ)

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • General Mathematics
  • Engineering (miscellaneous)

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