A novel enhanced quantum image representation based on bit-planes for log-polar coordinates

2022 ◽  
Vol 22 (1&2) ◽  
pp. 17-37
Author(s):  
Xiao Chen ◽  
Zhihao Liu ◽  
Hanwu Chen ◽  
Liang Wang
Keyword(s):  
Color Image ◽  
Image Representation ◽  
Polar Coordinates ◽  
Quantum Cost ◽  
Color Information ◽  
Simulation Experiments ◽  
Quantum Image ◽  
Comparison Results ◽  
Bit Planes ◽  
Quantum Image Representation

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.

scholarly journals An improved novel quantum image representation and its experimental test on IBM quantum experience

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jie Su ◽  
Xuchao Guo ◽  
Chengqi Liu ◽  
Shuhan Lu ◽  
Lin Li
Keyword(s):  
Image Processing ◽  
Information Processing ◽  
Quantum Information ◽  
Quantum Information Processing ◽  
Image Representation ◽  
Reference Value ◽  
Vertical Position ◽  
Quantum Image ◽  
Quantum Image Representation ◽  
Ibm Quantum Experience

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.

QIRHSI: novel quantum image representation based on HSI color space model

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Guang-Long Chen ◽  
Xian-Hua Song ◽  
Salvador E. Venegas-Andraca ◽  
Ahmed A. Abd El-Latif
Keyword(s):  
Image Representation ◽  
Color Space ◽  
Quantum Image ◽  
Space Model ◽  
Hsi Color Space ◽  
Quantum Image Representation

scholarly journals A Quantum Image Representation Based on Bitplanes

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

A theoretical framework for quantum image representation and data loading scheme

2014 ◽  
Vol 57 (3) ◽  
pp. 1-11 ◽  
Author(s):  
BenQiong Hu ◽  
XuDong Huang ◽  
RiGui Zhou ◽  
YanYu Wei ◽  
Qun Wan ◽  
...  
Keyword(s):  
Image Representation ◽  
Theoretical Framework ◽  
Quantum Image ◽  
Data Loading ◽  
Quantum Image Representation ◽  
Loading Scheme

Image Processing Using Quantum Computing

2021 ◽  
pp. 186-201
Author(s):  
Bably Dolly ◽  
Deepa Raj
Keyword(s):  
Image Processing ◽  
Quantum Computing ◽  
Image Representation ◽  
Research Papers ◽  
Quantum Image ◽  
Current Scenario ◽  
Pros And Cons ◽  
Recent Trends ◽  
Classical Image ◽  
Quantum Image Representation

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.

Multi-Channel Quantum Image Scrambling

2016 ◽  
Vol 20 (1) ◽  
pp. 163-170 ◽  
Author(s):  
Fei Yan ◽  
◽  
Yiming Guo ◽  
Abdullah M. Iliyasu ◽  
Zhengang Jiang ◽  
...  
Keyword(s):  
Quantum Computing ◽  
Information Hiding ◽  
Reliable Method ◽  
Color Image ◽  
Image Scrambling ◽  
Simulation Experiments ◽  
Quantum Image ◽  
Image Information ◽  
Geometric Transformations ◽  
Quantum Image Scrambling

Image scrambling is a technique used for confidential storage and transmission as well as for image information hiding. In this study, we propose a multi-channel quantum image scrambling method, which applies both color and geometric transformations of an image. This is a simple and reliable method for transforming a meaningful quantum image into a meaningless or disordered one. We performed two simulation experiments, which demonstrated the efficiency and flexibility of the proposed method. Previous studies mainly developed scrambling strategies for grayscale quantum images, whereas the proposed method is effective for the color image scrambling in the quantum computing domain.

scholarly journals RESEARCH OF IMAGES FILTRATION METHODS IN COMPUTER SYSTEMS

2021 ◽  
Vol 5 (1) ◽  
pp. 93-99
Author(s):  
Oleksandr Tymochko ◽  
Volodymyr Larin ◽  
Maksym Kolmykov ◽  
Oleksander Timochko ◽  
Vladislava Pavlenko
Keyword(s):  
Color Image ◽  
Image Representation ◽  
Color Space ◽  
Visual Image ◽  
Color Model ◽  
Color Information ◽  
Color Formation ◽  
Rgb Color Space ◽  
Human Eyes ◽  
Three Components

It is known that human eyes are less sensitive to color, than to their brightness. In the RGB color space, all three components are considered equally important, and they are usually stored with the same resolution. However, you can display a color image more efficiently, separating the brightness from color information and presenting it with a higher resolution than color. RGB space is well suited for computer graphics, because it uses these three components for color formation. However, RGB space is not very effective when it comes to real images. The fact is that to save the color of an image, you need to know and store all three components of the RGB, and if one of them is missing, it will greatly distort the visual image representation. Also, when processing images in RGB space, it is not always convenient to perform any pixel conversion, because, in this case, it will be necessary to list all three values of the RGB component and write back. This greatly reduces the performance of various image processing algorithms. For these and other reasons, many video standards use brightness and two signals that carry information about the red and blue components of the signal, as a color model other than RGB. The most famous among such spaces is YCbCr.

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