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X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging

X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging

Published on: September 11, 2011

Multiple exposure fusion for high dynamic range image acquisition.

Takao Jinno¹, Masahiro Okuda

¹Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu, Japan.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|July 5, 2011

Summary

This summary is machine-generated.

This study introduces a new method for creating high dynamic range images (HDRIs) by fusing multiple exposures. The technique effectively reduces motion blur and ghosting artifacts, even with significant object movement.

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Area of Science:

Computer Vision
Image Processing
Computational Photography

Background:

High dynamic range imaging (HDRI) enhances image detail by combining multiple exposures.
Standard HDRI acquisition is susceptible to motion blur and ghosting artifacts due to object movement.
Accurate pixel irradiance estimation is crucial for effective HDRI construction.

Purpose of the Study:

To propose an efficient and accurate multiple exposure fusion technique for high dynamic range image (HDRI) acquisition.
To address and mitigate motion blur and ghosting artifacts in HDRI.
To develop a method that simultaneously estimates image displacements and problematic regions.

Main Methods:

A novel multiple exposure fusion technique is presented for HDRI.
Maximum a posteriori (MAP) estimation is employed to simultaneously estimate displacements and occlusion/saturation regions.
A new weighting scheme is proposed for the multiple image fusion process.

Main Results:

The proposed method constructs motion-blur-free high dynamic range images (HDRIs).
The algorithm demonstrates accuracy even when dealing with images exhibiting large object motion.
Simultaneous estimation of displacements and problematic regions effectively reduces artifacts.

Conclusions:

The developed multiple exposure fusion technique offers an efficient and accurate solution for HDRI acquisition.
The method successfully overcomes common challenges like motion blur and ghosting.
This approach enhances the quality and reliability of high dynamic range images, particularly in dynamic scenes.