Quantum Image Fusion Methods for Remote Sensing

Background

Image fusion is an image processing technique that has grown in prevalence in recent years. Image fusion can be used for many different applications including medical imaging, aerospace, remote sensing, military surveillance, and manufacturing flaw identification. Quantum image fusion is a more recent development that uses quantum computing techniques improve image quality. However, previous methods were found to yield relatively low accuracy.

Invention Description

Researchers at Arizona State University have developed a new quantum image fusion technique used for identifying and classifying objects obtained from C-band synthetic aperture radar (SAR) and optical images. This method involves a four-qubit quantum circuit that is used to process the SAR image dataset. This method was shown to enhance the spectral details not seen when using the raw SAR dataset. In addition to the quantum circuit, this method includes deep neural networks (NN) to improve classification results.

Potential Applications

• Remote sensing
• Synthetic aperture radar (SAR)
• Medical imaging
• Aerospace

Benefits and Advantages

• Improves classification results through deep neural networks
• Lowers size, weight, and power requirements of the system
• Reduced cost
• Enhances spectral details

Related Publication: Quantum Image Fusion Methods for Remote Sensing