Statistical modeling of images plays a crucial role in modern image processing tasks like segmentation, object detection and restoration. Although Gaussian distributions are conve...
A novel framework for spatially estimating unknown image data is presented. Common applications include inpainting, concealment of transmission errors, prediction in video coding,...
Haricharan Lakshman, Patrick Ndjiki-Nya, Martin K&...
In this paper we present a probabilistic framework for tracking objects based on local dynamic segmentation. We view the segn to be a Markov labeling process and abstract it as a ...
— Process variations in digital circuits make sequential circuit timing validation an extremely challenging task. In this paper, a Statistical Bellman-Ford (SBF) algorithm is pro...
Due to multipath delay spread and relatively high sampling rate in OFDM systems, the channel estimation is formulated as a sparse recovery problem, where a hybrid compressed sensi...