Browsing Division of Electrical, Electronics, and Computer Science (EECS) by Advisor "Chaudhury, Kunal Narayan"
Now showing items 1-10 of 10
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Efficient and Convergent Algorithms for High-Fidelity Hyperspectral Image Fusion
Hyperspectral (HS) imaging refers to acquiring images with hundreds of bands corresponding to different wavelengths of light. HS imaging has a wide range of applications such as remote sensing, industrial inspection, ... -
A Fast Constant-Time Approximation for Locally Adaptive Bilateral Filtering
Smoothing is a fundamental task in low-level image processing that is used to suppress irrelevant details while preserving salient image structures. The simplest smoothing mechanism is to average neighboring pixels using ... -
Fast High-Dimensional Filtering
Smoothing (diffusion) is a fundamental task in low-level vision and image processing. In the context of natural images, where edges (sharp discontinuities) play an important psychovisual role, the smoothing process needs ... -
Hyperspectral Image Fusion with Implicit Regularization
Hyperspectral (HS) satellite images contain rich spectral information but generally suffer from low spatial resolution. In contrast, multispectral (MS) images offer higher spatial resolution but only a limited number of ... -
Kernel-Based Image Filtering: Fast Algorithms and Applications
Image filtering is a fundamental preprocessing task in computer vision and image processing. Various linear and nonlinear filters are routinely used for enhancement, upsampling, sharpening, reconstruction, etc. The focus ... -
Multiview Registration Using Rank-Constrained Semide nite Programming
We consider the problem of reconstructing a 3D surface from its multiview scans. Typically, the computational pipeline for this problem has two phases: (I) finding point-to-point correspondences between overlapping scans, ... -
On a Divide-and-Conquer Approach for Sensor Network Localization
(2018-08-20)Advancement of micro-electro-mechanics and wireless communication have proliferated the deployment of large-scale wireless sensor networks. Due to cost, size and power constraints, at most a few sensor nodes can be equipped ... -
On Plug-and-Play Regularization using Linear Denoisers
The problem of inverting a given measurement model comes up in several computational imaging applications. For example, in CT and MRI, we are required to reconstruct a high-resolution image from incomplete noisy measurements, ... -
Provably Convergent Algorithms for Denoiser-Driven Image Regularization
Some fundamental reconstruction tasks in image processing can be posed as an inverse problem where we are required to invert a given forward model. For example, in deblurring and superresolution, the ground-truth image ... -
Theoretical and Algorithmic Aspects of Rigid Registration
In this thesis, we consider the rigid registration problem, which arises in applications such as sensor network localization, multiview registration, and protein structure determination. The abstract setup for this problem ...