Optimizing fast fourier transform (FFT) image compression using intelligent water drop (IWD) algorithm

  1. Surinder Kaur 1
  2. Gopal Chaudhary 1
  3. Javalkar Dinesh Kumar
  4. Manu S. Pillai 1
  5. Yash Gupta 1
  6. Manju Khari 2
  7. Vicente García-Díaz 3
  8. Javier Parra Fuente 4
  1. 1 Bharati Vidyapeeth’s College of Engineering
  2. 2 Jawaharlal Nehru University
    info

    Jawaharlal Nehru University

    Nueva Delhi, India

    ROR https://ror.org/0567v8t28

  3. 3 Universidad de Oviedo
    info

    Universidad de Oviedo

    Oviedo, España

    ROR https://ror.org/006gksa02

  4. 4 Universidad Inernacional de La Rioja
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Revista:
IJIMAI

ISSN: 1989-1660

Any de publicació: 2022

Volum: 7

Número: 7

Pàgines: 48-55

Tipus: Article

DOI: 10.9781/IJIMAI.2022.01.004 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Altres publicacions en: IJIMAI

Objectius de Desenvolupament Sostenible

Resum

Digital image compression is the technique in digital image processing where special attention is provided in decreasing the number of bits required to represent a digital image. A wide range of techniques have been developed over the years, and novel approaches continue to emerge. This paper proposes a new technique for optimizing image compression using Fast Fourier Transform (FFT) and Intelligent Water Drop (IWD) algorithm. IWD-based FFT Compression is a emerging ethodology, and we expect compression findings to be much better than the methods currently being applied in the domain. This work aims to enhance the degree of compression of the image while maintaining the features that contribute most. It optimizes the FFT threshold values using swarm-based optimization technique (IWD) and compares the results in terms of Structural Similarity Index Measure (SSIM). The criterion of structural similarity of image quality is based on the premise that the human visual system is highly adapted to obtain structural information from the scene, so a measure of structural similarity provides a reasonable estimate of the perceived image quality.

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