The need to increase the complexity of computational methods to produce improvements in functional performance, particularly in medical image processing applications, leads to find suitable physical devices. This chapter describes two ways of adapting the techniques of image processing to quantum devices. This kind of computing can achieve, for some problems, unparalleled performance as compared to classic computing. In the first method, using the quantum Grover’s algorithm how to implement image processing techniques under quantum rules is shown. In the second method, using diffraction and interference, the possibility of using less complex quantum devices for processing digital images is treated. Using leucocytes images, that mode is test...
In the field of quantum imaging one takes advantage of the quantum aspects of light and of the intri...
This source code is meant to support the understanding of our paper Improved FRQI on superconducting...
In this paper, the authors present a new approach for image processing based on reverse emergence an...
A flexible representation of quantum images (FRQI) was proposed to facilitate the extension of class...
Processing of digital images is continuously gaining in volume and relevance, with concomitant deman...
Developing new computing methods and signal processing algorithms by borrowing from the principle of...
Histogram plays an important statistical role in digital image processing. However, the existing qua...
Abstract Hybrid quantum systems have shown promise in image classification by combining the strength...
Developing new computing methods and signal processing algorithms byborrowing from the principle of ...
AbstractThree design strategies for constructing new geometric transformations on quantum images fro...
In this study, a powerful representation of Quantum Images (PRQI) is proposed to represent images in...
Quantum Machine learning is a promising technology that is related to the study of computing. Due to...
Quantum Imaging is a newly born branch of quantum optics that investigates the ultimate performance ...
Face recognition is one of the most ubiquitous examples of pattern recognition in machine learning, ...
In order to solve the problems of pixel distortion, image clarity, and detail reduction during rever...
In the field of quantum imaging one takes advantage of the quantum aspects of light and of the intri...
This source code is meant to support the understanding of our paper Improved FRQI on superconducting...
In this paper, the authors present a new approach for image processing based on reverse emergence an...
A flexible representation of quantum images (FRQI) was proposed to facilitate the extension of class...
Processing of digital images is continuously gaining in volume and relevance, with concomitant deman...
Developing new computing methods and signal processing algorithms by borrowing from the principle of...
Histogram plays an important statistical role in digital image processing. However, the existing qua...
Abstract Hybrid quantum systems have shown promise in image classification by combining the strength...
Developing new computing methods and signal processing algorithms byborrowing from the principle of ...
AbstractThree design strategies for constructing new geometric transformations on quantum images fro...
In this study, a powerful representation of Quantum Images (PRQI) is proposed to represent images in...
Quantum Machine learning is a promising technology that is related to the study of computing. Due to...
Quantum Imaging is a newly born branch of quantum optics that investigates the ultimate performance ...
Face recognition is one of the most ubiquitous examples of pattern recognition in machine learning, ...
In order to solve the problems of pixel distortion, image clarity, and detail reduction during rever...
In the field of quantum imaging one takes advantage of the quantum aspects of light and of the intri...
This source code is meant to support the understanding of our paper Improved FRQI on superconducting...
In this paper, the authors present a new approach for image processing based on reverse emergence an...