Quantum Image Processing: The Future of High-Speed Computation

Authors

  • Hira Shafiq Department of Computer Science, Institute of southern Punjab, Multan, Pakistan.
  • Sindhu Department of Software Engineering, Muhammad Ali Jinnah University, Karachi, Pakistan
  • Naila Sher Afzal Department of Computer Science & IT, University of Kotli Azad Jammu and Kashmir, Pakistan.
  • Ishtiaq Ahmed Department of Computer Science & IT, University of Kotli Azad Jammu and Kashmir, Pakistan.
  • Mehtab Mushtaq Department of Computer Science & IT, University of Kotli Azad Jammu and Kashmir, Pakistan.
  • Muhammad Saeed Department of Computer Science & IT, University of Kotli Azad Jammu and Kashmir, Pakistan.

DOI:

https://doi.org/10.62019/z3xqhe82

Abstract

The Quantum Image Processing (QIP, based on developing along quantum computing and digital image analysis) is an emerging field. Due to the growing needs for image processing with high speed and efficiency in applications including medical imaging, satellite surveillance, autonomous vehicle, and big data analytics, there are limitations of scalability and speed with classical methods. By exploring the very principles on which the modern world operates, from superposition to entanglement, quantum computing provides an altogether transformative perspective on how to process and analyze images exponentially faster. QIP is the topic of this paper and how it might change the way that images are stored, processed, and interpreted; that is, we look at the theoretical foundations and practical considerations of QIP. Quantum representation of images, quantum Fourier transforms, and quantum edge detection are discussed. The challenges to technical and implementable aspects of QIP need not preclude the next generation of high speed computation. The objectives of this research include discovering the potential of QIP, and the weaknesses and future occurrence of the QIP technology.

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Published

2025-09-07

How to Cite

Quantum Image Processing: The Future of High-Speed Computation. (2025). The Asian Bulletin of Big Data Management , 5(3), 195-207. https://doi.org/10.62019/z3xqhe82