Prof. Vivek K. Goyal
at Boston Univ
SPIE Involvement:
Conference Program Committee | Conference Chair | Author | Editor | Instructor
Publications (14)

Proceedings Article | 9 September 2019
Proc. SPIE. 11138, Wavelets and Sparsity XVIII
KEYWORDS: Light sources, Digital photography, Computational imaging, Imaging systems, Opacity, Photography, Image resolution, Non-line-of-sight propagation, Passive remote sensing, Visibility, RGB color model

Proceedings Article | 24 August 2017
Proc. SPIE. 10394, Wavelets and Sparsity XVII
KEYWORDS: Photon counting, Super resolution, Computational imaging, Detection and tracking algorithms, LIDAR, Inverse problems, Reconstruction algorithms, Radar imaging

SPIE Conference Volume | 2 October 2015

SPIE Conference Volume | 24 October 2013

Proceedings Article | 26 September 2013
Proc. SPIE. 8858, Wavelets and Sparsity XV
KEYWORDS: Optical imaging, Photodetectors, Imaging systems, Sensors, Denoising, Computer simulations, Time correlated photon counting, Range imaging, Single photon detectors, Signal detection

Showing 5 of 14 publications
Conference Committee Involvement (7)
Wavelets and Sparsity XVIII
13 August 2019 | San Diego, California, United States
Wavelets and Sparsity XVII
6 August 2017 | San Diego, California, United States
Wavelets and Sparsity XVI
10 August 2015 | San Diego, California, United States
Wavelets and Sparsity XV
26 August 2013 | San Diego, California, United States
Wavelets and Sparsity XIV
21 August 2011 | San Diego, California, United States
Showing 5 of 7 published special sections
Course Instructor
SC203: Wavelets and Applications: State-of-the-Art
In this course, a comprehensive presentation of discrete and continuous wavelets, filter banks and subband coding, and multiresolution signal processing, is given. Techniques recently developed in different fields have converged to a unified theory. Wavelets provide an interesting alternative to Fourier transform methods. This course explains the successive approximation or multiresolution essential to wavelets and subhand coding: a signal can be seen as a coarse version plus added details.
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