scholarly journals Optimized Multi-Spectral Filter Array Based Imaging of Natural Scenes

Sensors ◽  
2018 ◽  
Vol 18 (4) ◽  
pp. 1172 ◽  
Author(s):  
Yuqi Li ◽  
Aditi Majumder ◽  
Hao Zhang ◽  
M. Gopi
Keyword(s):  
Natural Scenes ◽  
Spectral Filter ◽  
Filter Array

scholarly journals Spectral DiffuserCam: lensless snapshot hyperspectral imaging with a spectral filter array

Optica ◽  
2020 ◽  
Vol 7 (10) ◽  
pp. 1298 ◽  
Author(s):  
Kristina Monakhova ◽  
Kyrollos Yanny ◽  
Neerja Aggarwal ◽  
Laura Waller
Keyword(s):  
Hyperspectral Imaging ◽  
Spectral Filter ◽  
Filter Array

scholarly journals Spectral image recovery from Spectral Filter Array cameras using LMMSE

2019 ◽  
Vol 2019 (1) ◽  
pp. 300-303
Author(s):  
Prakhar Amba ◽  
David Alleysson
Keyword(s):  
Near Infrared ◽  
Minimum Mean Square Error ◽  
Spectral Filter ◽  
Spectral Image ◽  
Linear Solution ◽  
Recovery Method ◽  
Filter Array ◽  
Single Sensor ◽  
Stable Linear ◽  
Hyperspectral Camera

A hyperspectral camera can record a cube of data with both spatial 2D and spectral 1D dimensions. Spectral Filter Arrays (SFAs) overlaid on a single sensor allows a snapshot version of a hyperspectral camera. But acquired image is subsampled both spatially and spectrally, and a recovery method should be applied. In this paper we present a linear model of spectral and spatial recovery based on Linear Minimum Mean Square Error (LMMSE) approach. The method learns a stable linear solution for which redundancy is controlled using spatial neighborhood. We evaluate results in simulation using gaussian shaped filter's sensitivities on SFA mosaics of upto 9 filters with sensitivities both in visible and Near-Infrared (NIR) wavelength. We show by experiment that by using big neighborhood sizes in our model we can accurately recover the spectra from the RAW images taken by such a camera. We also present results on recovered spectra of Macbeth color chart from a Bayer SFA having 3 filters.

SPECTRAL MEASUREMENT AND CLASSIFICATION IN THE ERA OF BIG DATA

2021 ◽  
Author(s):  
F.S. Webler ◽  
M. Andersen
Keyword(s):  
Data Compression ◽  
Feature Space ◽  
Natural World ◽  
Natural Scenes ◽  
Scientific Disciplines ◽  
Multichannel Filter ◽  
Filter Array ◽  
Low Dimensional ◽  
Imaging Sensors

The measurement and classification of light is essential across many scientific disciplines. Devices used to measure light range from the highly precise scanning spectroradiometers to the more practical compact multichannel filter-array type imaging sensors and the ubiquitous RGB pixel. While there have been numerous successful efforts to reconstruct spectrum from RGB, RGB-to-spectrum reconstruction has historically been limited to natural scenes and other edge cases under strict constraints. However, information theory and recent advances in deep learning have shed new light on the vast amount of redundancy contained within data collected in the natural world, including light. In this paper, we will investigate how analytic methods can help map high dimensional spectra data to a low-dimensional feature space with minimal inductive bias. Through a better understanding of the intrinsic dimension of the data, we can use the features expressed in this representation to exploit regularities and make tasks like data compression, measurement and classification more efficient. The aim of this analysis is to help inform how and when low-dimensional representation of spectra is useful in practice for designing compact sensors as well as for lossy data compression and robust classification.

Design and fabrication of Fourier spectral filter array for multispectral imaging

2016 ◽  
Author(s):  
Chuan Ni ◽  
Jie Jia ◽  
Keigo Hirakawa ◽  
Andrew Sarangan
Keyword(s):  
Multispectral Imaging ◽  
Spectral Filter ◽  
Filter Array

HDR Imaging Pipeline for Spectral Filter Array Cameras

2017 ◽  
pp. 401-412
Author(s):  
Jean-Baptiste Thomas ◽  
Pierre-Jean Lapray ◽  
Pierre Gouton
Keyword(s):  
Spectral Filter ◽  
Filter Array

Guided Filter Demosaicking For Fourier Spectral Filter Array

2016 ◽  
Vol 2016 (2) ◽  
pp. 1-5 ◽  
Author(s):  
Jie Jia ◽  
Chuan Ni ◽  
Andrew Sarangan ◽  
Keigo Hirakawa
Keyword(s):  
Guided Filter ◽  
Spectral Filter ◽  
Filter Array

Fourier Spectral Filter Array for Optimal Multispectral Imaging

2016 ◽  
Vol 25 (4) ◽  
pp. 1530-1543 ◽  
Author(s):  
Jie Jia ◽  
Kenneth J. Barnard ◽  
Keigo Hirakawa
Keyword(s):  
Multispectral Imaging ◽  
Spectral Filter ◽  
Filter Array
Sign in / Sign up

Export Citation Format

Share Document