PERCEPTUAL NORMALIZED INFORMATION DISTANCE FOR IMAGE DISTORTION ANALYSIS BASED ON KOLMOGOROV COMPLEXITY

2011 ◽  
Author(s):  
Nima Nikvand ◽  
Zhou Wang ◽  
Ilias Kotsireas ◽  
Roderick Melnik ◽  
Brian West
Keyword(s):  
Kolmogorov Complexity ◽  
Image Distortion ◽  
Information Distance ◽  
Distortion Analysis

Image Distortion Analysis and Correction Study of AOTF Camera Imaging Process

2017 ◽  
Vol 54 (9) ◽  
pp. 091101
Author(s):  
吕泽 Lü Ze ◽  
陈友华 Chen Youhua ◽  
薛鹏 Xue Peng ◽  
王志斌 Wang Zhibin ◽  
陈媛媛 Chen Yuanyuan
Keyword(s):  
Image Distortion ◽  
Camera Imaging ◽  
Distortion Analysis

2-D Fitting and Interpolation Applied to Image Distortion Analysis

1983 ◽  
pp. 321-333
Author(s):  
Y. Bizais ◽  
I. G. Zubal ◽  
R. W. Rowe ◽  
G. W. Bennett ◽  
A. B. Brill
Keyword(s):  
Image Distortion ◽  
Distortion Analysis

Quantum information distance

2021 ◽  
Author(s):  
Songsong Dai
Keyword(s):  
Quantum Information ◽  
Turing Machine ◽  
Kolmogorov Complexity ◽  
Transition Program ◽  
Information Distance ◽  
Universal Turing Machine ◽  
Classical Setting ◽  
Universal Quantum ◽  
Definition Of ◽  
Quantum Turing Machine

In this paper, we give a definition for quantum information distance. In the classical setting, information distance between two classical strings is developed based on classical Kolmogorov complexity. It is defined as the length of a shortest transition program between these two strings in a universal Turing machine. We define the quantum information distance based on Berthiaume et al.’s quantum Kolmogorov complexity. The quantum information distance between qubit strings is defined as the length of the shortest quantum transition program between these two qubit strings in a universal quantum Turing machine. We show that our definition of quantum information distance is invariant under the choice of the underlying quantum Turing machine.

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