Introduction to Team N° 01 :
Overall Objectives :
Overall objectives of the ‘Image Processing and Applications’ team’s research are primarily focused on image denoising using recently developed high-performance algorithms, compression of still images and videos through powerful transformation and coding algorithms, and motion estimation in video images using differential methods and matching techniques combined with motion-based segmentation and inpainting. Optimization has become a crucial research direction, leading the team’s efforts towards optimizing compression and estimation through genetic algorithms and metaheuristic techniques, which have proven to be very effective in the field of optimization.
Applications of image processing in the economic and industrial sectors are numerous, including biomedical engineering, remote sensing, and data transmission. In this context, the ‘Image Processing and Applications’ team aims to propose solutions to the problems faced by relevant sectors at the local and national levels, such as hospitals (medical image archiving), meteorological stations (denoising and transmission of satellite images), and telecom services (image transmission and compression).
Scientific Foundations :
1- Motion Estimation in Video Imaging :
In this area, we focus on optical flow estimation, motion-based segmentation, and inpainting.
2- Compression of Still Images and Video:
In this area, we explore the compression of still images and videos using classical and geometric wavelet transforms associated with entropy coding and hierarchical algorithms.
3- Optimization:
In this area, we focus on optimizing motion estimation and compression using metaheuristic techniques and genetic algorithms.
4- Image Denoising:
In this area, we are concerned with image denoising through multi-resolution geometric transformations and approximate filtering algorithms.
