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Updated: Jun 7, 2026

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

IMAGE resolution enhancement by using discrete and stationary wavelet decomposition.

Hasan Demirel, Gholamreza Anbarjafari

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

|October 21, 2010

Summary

This study introduces an improved image resolution enhancement method using discrete wavelet transform (DWT) and stationary wavelet transform (SWT). The technique effectively enhances edges and details, outperforming existing resolution enhancement methods.

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Last Updated: Jun 7, 2026

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

Area of Science:

Digital Image Processing
Computer Vision
Signal Processing

Background:

Image resolution enhancement is crucial for various applications.
Traditional methods often struggle with preserving fine details and edge sharpness.

Discussion:

The proposed method utilizes discrete wavelet transform (DWT) for subband decomposition.
Stationary wavelet transform (SWT) is incorporated for intermediate edge enhancement.
Interpolation of high-frequency subbands and the input image refines details.

Key Insights:

The integration of DWT and SWT significantly improves edge details in super-resolved images.
The proposed interpolation strategy enhances high-frequency components effectively.
Quantitative and visual results demonstrate superior performance compared to existing techniques.

Outlook:

Further research could explore adaptive subband selection for varied image content.
Real-time implementation of this technique could be investigated for video processing.
Investigating the impact of different wavelet families may yield further improvements.