Fractional Transform Methods in Complexity Analysis: Theory and Image Applications
A special issue of Fractal and Fractional (ISSN 2504-3110). This special issue belongs to the section "Complexity".
Deadline for manuscript submissions: 31 December 2026 | Viewed by 12
Special Issue Editor
Special Issue Information
Dear Colleagues,
The integration of fractional transform methods with complexity analysis has become a pivotal, fast-evolving research frontier at the intersection of applied mathematics, signal processing, and computer science. It enriches complexity quantification theory—using fractional transforms’ non-local, memory-dependent properties to capture intricate dynamics—and advances image applications (enhancing feature extraction, noise-robust analysis, etc.), with impacts on medical imaging (e.g., tumor characterization), remote sensing, and industrial defect detection.
This Special Issue requests high-quality papers covering the following: novel fractional transform paradigms (e.g., fractional Fourier/wavelet transforms) for complexity quantification; theoretical explorations of fractional transform-enhanced complexity metrics (e.g., entropy); image applications such as denoising, segmentation, and content security; comparative/validation studies of fractional vs. traditional methods in image scenarios. Cross-disciplinary studies on complexity analysis and applications (e.g., integrating with machine learning for intelligent image interpretation) are also encouraged. Comprehensive review articles on the field’s progress, challenges, and future directions will also be considered.
Dr. Hao Zhang
Guest Editor
Manuscript Submission Information
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Keywords
- complexity analysis
- fractional theory
- fractals theory
- nonlinear dynamics
- image encryption and coding
- image compression
- image watermarking and information hiding
- image segmentation and processing
- control and stability with complexities
- AI methods in image processing
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