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William Clement Karl
Researcher at Boston University
Publications - 178
Citations - 5483
William Clement Karl is an academic researcher from Boston University. The author has contributed to research in topics: Iterative reconstruction & Image segmentation. The author has an hindex of 37, co-authored 176 publications receiving 5252 citations. Previous affiliations of William Clement Karl include National Heart Foundation of Australia & Massachusetts Institute of Technology.
Papers
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Journal ArticleDOI
Feature-enhanced synthetic aperture radar image formation based on nonquadratic regularization
TL;DR: This work develops a method for the formation of spotlight-mode synthetic aperture radar (SAR) images with enhanced features based on a regularized reconstruction of the scattering field which combines a tomographic model of the SAR observation process with prior information regarding the nature of the features of interest.
Journal ArticleDOI
Sparsity-Driven Synthetic Aperture Radar Imaging: Reconstruction, autofocusing, moving targets, and compressed sensing
Mujdat Cetin,Ivana Stojanovic,Özben Naime Önhon,Kush R. Varshney,Sadegh Samadi,William Clement Karl,Alan S. Willsky +6 more
TL;DR: A survey of recent research on sparsity-driven synthetic aperture radar (SAR) imaging, including the analysis and synthesis-based sparse signal representation formulations for SAR image formation, and recent work on compressed sensing (CS)-based analysis and design of SAR sensing missions.
Proceedings ArticleDOI
Probabilistic video stabilization using Kalman filtering and mosaicing
TL;DR: This paper presents a new image processing method to remove unwanted vibrations and reconstruct a video sequence void of sudden camera movements based on a probabilistic estimation framework, and shows a significant improvement in stabilization quality.
Proceedings ArticleDOI
Real-time tracking using level sets
TL;DR: A novel implementation of the level set method that achieves real-time level-set-based video tracking is proposed and a novel procedure based on Gaussian filtering is introduced to incorporate boundary smoothness regularization.
Journal ArticleDOI
A Real-Time Algorithm for the Approximation of Level-Set-Based Curve Evolution
TL;DR: A two-cycle algorithm to approximate level-set-based curve evolution without the need of solving partial differential equations (PDEs) is proposed, applicable to a broad class of evolution speeds that can be viewed as composed of a data-dependent term and a curve smoothness regularization term.