Log In Sign Up

SASSI – Super-Pixelated Adaptive Spatio-Spectral Imaging

by   Vishwanath Saragadam, et al.

We introduce a novel video-rate hyperspectral imager with high spatial, and temporal resolutions. Our key hypothesis is that spectral profiles of pixels in a super-pixel of an oversegmented image tend to be very similar. Hence, a scene-adaptive spatial sampling of an hyperspectral scene, guided by its super-pixel segmented image, is capable of obtaining high-quality reconstructions. To achieve this, we acquire an RGB image of the scene, compute its super-pixels, from which we generate a spatial mask of locations where we measure high-resolution spectrum. The hyperspectral image is subsequently estimated by fusing the RGB image and the spectral measurements using a learnable guided filtering approach. Due to low computational complexity of the superpixel estimation step, our setup can capture hyperspectral images of the scenes with little overhead over traditional snapshot hyperspectral cameras, but with significantly higher spatial and spectral resolutions. We validate the proposed technique with extensive simulations as well as a lab prototype that measures hyperspectral video at a spatial resolution of 600 × 900 pixels, at a spectral resolution of 10 nm over visible wavebands, and achieving a frame rate at 18fps.


page 5

page 7

page 8

page 9

page 10

page 14

page 16

page 17


Fast and robust pushbroom hyperspectral imaging via DMD-based scanning

We describe a new pushbroom hyperspectral imaging device that has no mac...

Programmable Spectrometry -- Per-pixel Classification of Materials using Learned Spectral Filters

Many materials have distinct spectral profiles. This facilitates estimat...

On Space-spectrum Uncertainty Analysis for Coded Aperture Systems

We introduce and analyze the concept of space-spectrum uncertainty for c...

Toward Efficient Hyperspectral Image Processing inside Camera Pixels

Hyperspectral cameras generate a large amount of data due to the presenc...

Spectral video construction from RGB video: Application to Image Guided Neurosurgery

Spectral imaging has received enormous interest in the field of medical ...

KRISM --- Krylov Subspace-based Optical Computing of Hyperspectral Images

Low-rank modeling of hyperspectral images has found extensive use in num...

Hyperspectral recovery from RGB images using Gaussian Processes

Hyperspectral cameras preserve the fine spectral details of scenes that ...