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Related Experiment Video

Updated: May 25, 2026

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

FAST EDGE-FILTERED IMAGE UPSAMPLING.

Shantanu H Joshi¹, Antonio L Marquina, Stanley J Osher

¹Laboratory of Neuro Imaging, University of California, Los Angeles, CA 90095, USA.

Proceedings. International Conference on Image Processing

|February 11, 2012

Summary

This summary is machine-generated.

This study introduces a new image upsampling method that preserves edges for faster processing. The technique enhances image details and sharpens boundaries while maintaining smooth areas, outperforming existing methods.

Related Experiment Videos

Last Updated: May 25, 2026

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

Area of Science:

Computer Vision
Image Processing
Numerical Analysis

Background:

Image upsampling is crucial for enhancing image resolution.
Existing interpolation methods often struggle to preserve sharp edges and introduce artifacts.
Fast and accurate image interpolation remains an active research area.

Purpose of the Study:

To develop a novel, edge-preserved interpolation scheme for efficient natural image upsampling.
To improve the quality of upsampled images by enhancing edges and maintaining smooth regions.
To provide a faster alternative to traditional interpolation techniques.

Main Methods:

A piecewise hyperbolic operator with a slope-limiter function was employed.
The operator facilitates higher-order approximations for improved accuracy.
Spatial oscillations near edges and discontinuities are restricted.

Main Results:

The proposed method successfully preserves and enhances edges and boundaries in upsampled images.
Smoothly varying features within images are maintained effectively.
Experimental results demonstrate improved Peak Signal-to-Noise Ratio (PSNR) compared to cubic and spline interpolation.

Conclusions:

The novel interpolation scheme offers superior edge preservation and detail enhancement for image upsampling.
The method provides a computationally efficient approach to high-quality image resizing.
This technique represents a significant advancement in digital image processing.