Talks
New Results in Image Processing Based on Sparse & Redundant Representations
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In this very brief talk I describe the need to model images in general, and then briefly present the Sparse-Land model. The talk includes a demonstration of a sequence of applications in image processing where this model has been deployed successfully, including denoising of still, color and video images, inpainting, and compression. The moral to take home is: “The Sparse-Land model is a new and promising model that can adapt to many types of data sources. Its potential for medical imaging is an important opportunity that should be explored”.