Strategy for quantum image stabilization

Abstract

Image stabilization is a process to smooth the unstable motion vector of video sequences to achieve its stabilization. Even though the classical image stabilization techniques seem already very mature so far, similar advances have not been extended to the quantum computing domain. In this study, we explore a novel quantum video framework and make a modest attempt to perform the image stabilization based on it by utilizing the quantum comparator and quantum image translation operations. The proposed method is capable of estimating the camera motion during exposure and compensating for the video jitter caused by the motion. In addition, the quantum properties, i.e., entanglement and parallelism, ensure that the quantum image stabilization is feasible and effective. Finally, a simple experiment to stabilize a four-frame jittered quantum video is implemented using Matlab based on linear algebra with complex vectors as quantum states and unitary matrices as unitary transforms to show the feasibility and merits of this proposal.

School of Teacher, Nanjing Xiao Zhuang University, Nanjing, 210000, China

“…Among them, the NEQR model is widely used due to its simplicity of operation. Based on different quantum image representation models, the corresponding QIP algorithms also develop rapidly, such as geometrical transformation of quantum image [13], quantum image encryption [14], feature extraction of quantum image [15], quantum image scrambling [16], quantum image morphological operations [17], quantum image watermarking [18], quantum image filtering [19], quantum image steganography [20], quantum image stabilization [21], quantum image bilinear interpolation [22], quantum image edge detection [23][24][25][26], quantum image segmentation [27][28][29], etc. Although the research of quantum image processing technology is gradually deepening, it is still in the initial stage as a whole, and the development direction is not balanced.…”

Circuit-Based Modular Implementation of Quantum Ghost Imaging

“…COM) circuit has been widely used in quantum computing literature. Designed in [37] and as used in [38], the COM module (Figure 2) compares two states |y and |x , where |y = |y n−1 . .…”

A Quantum Moving Target Segmentation Algorithm for Grayscale Video

“…This is also the only work to study quantum moving target detection algorithm to date. In the same year, they [12] proposed a quantum video stabilization strategy and they used quantum comparators and quantum image translation operations to estimate the motion during exposure and to compensate for motion-induced video jitter. In 2020, Song et al [16] proposed a quantum video encryption scheme based on the new quantum video framework, the controlled-XOR operation, and the improved logic mapping.…”

“…[ 10 ] Among them, QVNEQR stores video information (frames and pixels) in the base state of qubits, which makes the operation of pixels in video simpler, so it has been widely used. At present, research on quantum video mainly focuses on quantum video representation, [ 8–10 ] moving target detection, [ 10,11 ] quantum video stabilization, [ 12 ] and quantum video encryption. [ 13–16 ]…”