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Malena Espanol, Arizona State University
In today's visually-centric world, the demand for high-quality images is ever-increasing, whether it is for medical imaging, surveillance, or digital photography. However, the process of capturing images is inherently prone to blurring due to various factors, such as motion during capture or imperfections in optical systems. The image deblurring problem lies at the heart of restoring these blurred images to their sharp, clear originals, presenting an exciting challenge for mathematicians. In this project, we will leverage tools and concepts from linear algebra, statistics, and optimization to produce new, efficient, and accurate algorithms. Furthermore, we will explore the use of wavelets and multilevel methods to speed up the process of restoring images.
Final Report