S. Kim, H. Lim, D.N. Kim, and M. Tynan (USA)
Subjectmodularization,imagedenoising, zooming, segmentation, anisotropic diffusion, mathemati cal image processing.
This article is concerned with a new mentoring strat egy, called subject modularization (SM), for high school students to be able to make a fundamental contribution to research in mathematical image processing. In SM, both mathematical subjects and software are partitioned into small modules, each of which is simple and easy enough to be manageable for talented high school students. Then, the students can finish a research project successfully by resolving a series of easy-to-solve problems. Also we consider an effective strategy for mentors to be able to provide a balance of support so that the students can have a reasonable share of the work and make significant contributions to interdisciplinary research in applied mathematics. Through the project, two high school students have developed new mathematical models and corresponding numerical schemes for efficient and reliable image processing in denoising and segmentation, which are publishable to an academic journal. Various examples carried out by the students are shown to demonstrate ef fectiveness of the newly developed models and numerical schemes.
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