In this paper, following the Compressed Sensing (CS) paradigm, we study the problem of recovering sparse or compressible signals from uniformly quantized measurements. We present ...
We address the problem of real-time mode decisions for enhancement layer coding in the context of fine granularity scalable coding. While traditional mode selection strategies tak...
Compressive Sensing is an emerging field based on the revelation that a small group of non-adaptive linear projections of a compressible signal contains enough information for rec...
Michael B. Wakin, Jason N. Laska, Marco F. Duarte,...
Images taken from scenes under water suffer distortion due to refraction. While refraction causes magnification with mild distortion on the observed images, severe distortions in...
This paper introduces a novel image-based rendering method which uses inputs from unstructured cameras and synthesizes free-viewpoint images of high quality. Our method uses a set...