Image preparations of multi-mode quantum image representation and their application on quantum image reproduction

Optik ◽  
2021 ◽  
pp. 168321
Author(s):  
Hai-Hua Zhu ◽  
Xiu-Bo Chen ◽  
Yi-Xian Yang
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jie Su ◽  
Xuchao Guo ◽  
Chengqi Liu ◽  
Shuhan Lu ◽  
Lin Li

AbstractQuantum image representation (QIR) is a necessary part of quantum image processing (QIP) and plays an important role in quantum information processing. To address the problems that NCQI cannot handle images with inconsistent horizontal and vertical position sizes and multi-channel image processing, an improved color digital image quantum representation (INCQI) model based on NCQI is proposed in this paper. The INCQI model can process color images and facilitate multi-channel quantum image transformations and transparency information processing of images using auxiliary quantum bits. In addition, the quantum image control circuit was designed based on INCQI. And quantum image preparation experiments were conducted on IBM Quantum Experience (IBMQ) to verify the feasibility and effectiveness of INCQI quantum image preparation. The prepared image information was obtained by quantum measurement in the experiment, and the visualization of quantum information was successfully realized. The research in this paper has some reference value for the research related to QIP.


2022 ◽  
Vol 22 (1&2) ◽  
pp. 17-37
Author(s):  
Xiao Chen ◽  
Zhihao Liu ◽  
Hanwu Chen ◽  
Liang Wang

Quantum image representation has a significant impact in quantum image processing. In this paper, a bit-plane representation for log-polar quantum images (BRLQI) is proposed, which utilizes $(n+4)$ or $(n+6)$ qubits to store and process a grayscale or RGB color image of $2^n$ pixels. Compared to a quantum log-polar image (QUALPI), the storage capacity of BRLQI improves 16 times. Moreover, several quantum operations based on BRLQI are proposed, including color information complement operation, bit-planes reversing operation, bit-planes translation operation and conditional exchange operations between bit-planes. Combining the above operations, we designed an image scrambling circuit suitable for the BRLQI model. Furthermore, comparison results of the scrambling circuits indicate that those operations based on BRLQI have a lower quantum cost than QUALPI. In addition, simulation experiments illustrate that the proposed scrambling algorithm is effective and efficient.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Guang-Long Chen ◽  
Xian-Hua Song ◽  
Salvador E. Venegas-Andraca ◽  
Ahmed A. Abd El-Latif

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 62396-62404 ◽  
Author(s):  
Hai-Sheng Li ◽  
Xiao Chen ◽  
Haiying Xia ◽  
Yan Liang ◽  
Zuoshan Zhou

2014 ◽  
Vol 57 (3) ◽  
pp. 1-11 ◽  
Author(s):  
BenQiong Hu ◽  
XuDong Huang ◽  
RiGui Zhou ◽  
YanYu Wei ◽  
Qun Wan ◽  
...  

Author(s):  
Bably Dolly ◽  
Deepa Raj

Image processing via the quantum platform is an emerging area for researchers. Researchers are more interested to move on towards quantum image processing instead of classical image processing. This chapter starts with the review of different quantum image computing-based research papers with a brief idea of the ethics which inspire quantum computing in the background and focus on the current scenario of recent trends of quantum image representation, pitfalls, and summarization of the pros and cons of it, with the limitations of the technologies used and focus on the recent work to be going on and application of it in a different field. In the next, it will focus on the different methods used by the researcher in the previous papers. The next section discussed the different methods based on quantum image representation used. Some different techniques of image storage, retrieval, and representation in a quantum system are discussed. Also, this chapter briefs the pros and cons of using different techniques in quantum systems in comparison to classical systems.


2021 ◽  
Author(s):  
Arijit Mandal ◽  
Shreya Banerjee ◽  
Prasanta K. Panigrahi

2016 ◽  
pp. 28-56 ◽  
Author(s):  
Sanjay Chakraborty ◽  
Lopamudra Dey

Image processing on quantum platform is a hot topic for researchers now a day. Inspired from the idea of quantum physics, researchers are trying to shift their focus from classical image processing towards quantum image processing. Storing and representation of images in a binary and ternary quantum system is always one of the major issues in quantum image processing. This chapter mainly deals with several issues regarding various types of image representation and storage techniques in a binary as well as ternary quantum system. How image pixels can be organized and retrieved based on their positions and intensity values in 2-states and 3-states quantum systems is explained here in detail. Beside that it also deals with the topic that focuses on the clear filteration of images in quantum system to remove unwanted noises. This chapter also deals with those important applications (like Quantum image compression, Quantum edge detection, Quantum Histogram etc.) where quantum image processing associated with some of the natural computing techniques (like AI, ANN, ACO, etc.).


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