In human eyes, retina cells have shown complicated, sophisticated structures, and thus capability of carrying out certain basic visual functions. In computer vision, a spherical model has been proposed to demonstrate that certain basic visual functions can be performed at the sensor/photoreceptor level for target recognition, mobile robotic control, and other applications. This paper will establish that low level computer vision in this spherical model exhibits a Hamiltonian model of quantum computation. This results will be important to the understanding of human vision as well as the development of intelligent visual sensor chips and devices in electronics and optics.
In human eyes, retina cells have shown complicated, sophisticated structures, and thus capability of carrying out certain basic visual functions. In computer vision, a spherical model has been proposed to demonstrate that certain basic visual functions can be performed at the sensor/photoreceptor level for target recognition, mobile robotic control, and other applications. This paper will establish that low level computer vision in this spherical model exhibits a Hamiltonian model of quantum computation. This results will be important to the understanding of human vision as well as the development of intelligent visual sensor chips and devices in electronics and optics.
The human eye contains millions of rod photoreceptor cells, and each one is a single-photon detector. Whether people can actually see a single photon|which requires the rod signal to propagate through the rest of the noisy visual system and be perceived in the brain|has been the subject of research for nearly 100 years. Early experiments hinted that people could see just a few photons, but classical light sources are poor tools for answering these questions. Single-photon sources have opened up a new area of vision research, providing the best evidence yet that humans can indeed see single photons, and could even be used to test quantum effects through the visual system. We discuss our program to study the lower limits of human vision with a heralded single-photon source based on spontaneous parametric downconversion, and present two proposed experiments to explore quantum effects through the visual system: testing the perception of superposition states, and using a human observer as a detector in a Bell test.
The evolving understanding of the limits of human visual perception has advanced the development of optical devices that not only correct visual defects but also help manage changes in certain eye structures. As modern optical technologies allow precise control of the quantum properties of light, recent endeavours have started testing the quantum capabilities of human eye perception, proving that they can detect single photons. This paves the way for the application of quantum metrology and cryptography to medical imaging, with potential increase in precision and security.
Quantum Machine Learning (QML) promises the transformative potential in computer vision by utilizing quantum computing to facilitate faster high-dimensional data processing. In this paper, we will go through some of the recent works that employ QML for computer vision problems such as Image Segmentation, Classification, and Generation. Demonstrations aimed at showing where QML methods beat the state of art techniques in particular applications like facial recognition, medical imaging, and satellite imagery. QML aspires to make pathbreaking changes in a field limited by current hardware capabilities. This poster abstract summarizes the important studies, methodologies and findings to inform further research in this developing field.
A study published in Nature Communications demonstrated for the first time that humans can consciously detect a single light particle by directing a single photon, controlled by quantum optical technology (SPDC), onto the cornea of human subjects. Breaking the conventional wisdom regarding the necessity of multiple photons for perception, the study showed that subjects directly perceived a single photon with a probability significantly above statistical chance. The study discovered a priming process where the probability of detecting a second single photon is significantly enhanced for several seconds after detecting an initial single photon, proving that the human visual neural network is a marvelous system capable of filtering information at the absolute quantum limit. [Quantum Biology Society] How fine a physical stimulus can human senses detect? In particular, whether our vision, through which we see the world, can perceive the most fundamental physical limit—a single particle of light (single photon)—has been a major subject of debate in the scientific community for over 70 years. While it was known that a single photoreceptor (rod cell) in the retina responds to individual photons , it was conventionally believed that to consciously perceive light, at least a few photons must arrive simultaneously to overcome noise. However, a phenomenal study has been published proving that the human eye and brain can break through this absolute quantum mechanical limit. The paper titled "Direct detection of a single photon by humans," published as an open-access article in the international journal Nature Communications, provides an answer to this fundamental question. A research team led by Professor Alipasha Vaziri and Jonathan N. Tinsley from the University of Vienna, the Research Institute of Molecular Pathology (IMP) in Austria, and The Rockefeller University in the USA, successfully spearheaded this groundbreaking experiment. ■ A Single Shot of Light Created with Quantum Optical Technology To overcome the limitations of conventional light sources, the research team utilized a quantum optical technology called spontaneous parametric down-conversion (SPDC). Through this, they built a perfectly controlled heralded single-photon source and performed over 30,000 rigorous psychophysics-based experimental trials, shooting this single photon into the corneas of subjects inside a pitch-black dark chamber. ■ The Human Brain Performs Quantum Noise Canceling The results were astounding. The subjects accurately identified when a single photon was emitted with a probability significantly above statistical chance. Even though only a minuscule amount of quantum energy struck the retina, the human visual system and neural networks in the brain filtered this absolute minimum unit of information out of macroscopic noise and visually perceived it. ■ A Light Seen Once is Seen Better: The Priming Effect of the Visual System Even more interestingly, the researchers discovered that the probability of detecting a second single photon was temporarily and significantly enhanced within a time window of a few seconds immediately after a subject detected an initial single photon. The researchers analyzed this as a priming process where the presence of an earlier photon temporarily enhances the effective gain of the visual system. This study proves that a living organism's sensory organs are not merely chemical sensors but sophisticated biophysical systems that interact directly with the quantum world, the smallest unit in the natural world. This discovery provides a new understanding of the signal processing mechanisms of brain neural networks and is expected to open the door to entirely new research exploring human vision and the brain using quantum states of light. https://www.nature.com/articles/ncomms12172
The retina is a light-sensitive layer is structured at the plane outer segments of an array of millions of individual nano-antennas. Apparently, the retina is one of the best known quantum detectors with rod cells able to respond to a single photon. It seems, the retina is an excellent photon counter and quantum processing of information occurs within the retina and subsequent processing of information at the level of neural membranes decrease the quantum efficiency. In this article we review on some evidences of quantum processing in the retina and finally propose some proposal experiments and ideas to detect quantum superposition in the retina.
Quantum computing is increasingly being viewed as a promising direction for the future of image processing. Conventional approaches to image classification, enhancement, compression, and restoration, although highly developed, often struggle with scalability, computational complexity, and data security—especially when processing high-dimensional or sensitive visual information. This survey explores how quantum computing can help address these limitations through quantum image representation models such as FRQI and NEQR, variational quantum circuits, and hybrid quantum–classical architectures. The primary objective of this review is to present a clear and structured overview of the current state of quantum image processing (QIP). It discusses foundational representation models, emerging hybrid learning techniques, available software frameworks and simulators, benchmarking practices, and practical applications in areas such as medical imaging, remote sensing, and biometric security. Particular attention is given to solutions that are feasible on today’s NISQ-era hardware, including hybrid architectures and quantum-secured image processing schemes. The survey concludes by identifying existing challenges and outlining realistic future research directions. Overall, it emphasizes the practical importance of hybrid models, the need for standardized quantum-oriented benchmarks, and the growing potential of quantum-based security mechanisms for safeguarding visual data.