Image Restoration Using a Multilayered Quantum Backpropagation Neural Network

Authors:
Sankha Subhra Mukherjee;Raka Chowdhury;Siddhartha Bhattacharyya
Affiliations:
-;-;-
Venue:
CICN '11 Proceedings of the 2011 International Conference on Computational Intelligence and Communication Networks
Year:
2011

Citing 0
Cited 2

2013 Special Issue: Single-hidden-layer feed-forward quantum neural network based on Grover learning

Neural Networks
Adaptive-type servo controller utilizing a quantum neural network with qubit neurons

International Journal of Hybrid Intelligent Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

The problem of image restoration in presence of blur and noise has been a very important problem in the domain of digital image processing and computer vision. A quantum inspired back propagation neural network (QBPNN) architecture based on quantum gates (single qubit rotation gates and two qubit controlled-not gates) has been used and its back propagation learning formulae have been proposed in this article for the task of restoration of images from noisy and blurred perspectives. The superiority of the QBPNN architecture is clearly demonstrated in terms of convergence rate and speed as compared to the classical multilayer perceptron (MLP).