Marie LUONG

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