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Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator
Published on: January 28, 2019
Image modeling using interscale phase properties of complex wavelet coefficients.
1Signal Processing and Communications Group, Department of Engineering, University of Cambridge, Cambridge, UK. m.a.miller.02@cantab.net
Summary
This study introduces "derotated" wavelet coefficients, enhancing image modeling by improving correlations near edges. This approach boosts signal estimation for better image processing applications.
Area of Science:
- Image processing and signal analysis
- Wavelet transforms and multiresolution analysis
Background:
- Traditional wavelet transforms struggle with accurate signal estimation near image features.
- Interscale dependencies in wavelet coefficients are crucial for advanced image modeling.
Purpose of the Study:
- To develop an improved image modeling approach using modified wavelet coefficients.
- To enhance signal estimation accuracy, particularly around edges and ridges.
Main Methods:
- Utilizing the dual tree complex wavelet transform (DTCWT).
- Applying a phase rotation to DTCWT coefficients to create "derotated" coefficients.
- Analyzing the correlation properties of derotated coefficients compared to standard ones.
Main Results:
- Derotated coefficients exhibit increased correlation near edge and ridge features.
- This enhanced correlation leads to improved signal estimation in critical image areas.
- The findings provide a foundation for designing advanced image denoising algorithms.
Conclusions:
- Phase manipulation of wavelet coefficients offers a novel way to improve image modeling.
- Derotated coefficients are beneficial for signal estimation in complex image regions.
- The proposed method has direct implications for the development of effective image denoising techniques.
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