معرفی
Marie LUONG is a researcher at Université Sorbonne Paris Nord specializing in image processing and analysis. She is currently preparing her HDR (Habilitation à Diriger des Recherches), a prestigious post-doctoral qualification in the French academic system that demonstrates research independence and eligibility to supervise PhD students.
Her research focuses on two major interconnected domains:
- Image Quality Enhancement: Developing techniques inspired by Human Visual System mechanisms to address coding artifacts, noise, and resolution limitations
- Image Classification: Creating innovative methods based on sparse representation in transform domains to improve classification accuracy
Dr. LUONG's methodological contributions include:
- Four methods for addressing coding artifacts with a proposed Blockiness Visibility Measure
- Six innovative denoising approaches combining anisotropic filtering and machine learning
- Three example-based super-resolution methods, two integrating denoising in a unified optimization framework
- Four classification methods leveraging sparse representation in wavelet domains
Her research demonstrates significant practical applications in digital cinema technology and medical image diagnosis systems, translating theoretical advances into real-world solutions.
Academic leadership and mentoring:
- Co-supervised seven completed PhD theses
- Currently supervising two ongoing doctoral projects
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