Compressive spectral imaging based on hexagonal blue noise coded apertures
Hao Zhang, Xu Ma, and Gonzalo R. Arce

TL;DR
This paper introduces hexagonal blue noise coded apertures for CASSI systems, enhancing spectral imaging performance by increasing sensing matrix degrees of freedom and satisfying RIP conditions.
Contribution
It proposes a novel hexagonal blue noise coded aperture design that outperforms traditional square pixel coded apertures in spectral imaging.
Findings
Hexagonal blue noise coded apertures improve sensing matrix properties.
The proposed method satisfies RIP with high probability.
The approach demonstrates superior spectral imaging performance.
Abstract
Coded aperture snapshot spectral imager (CASSI) is a computational imaging system that acquires a three dimensional (3D) spectral data cube by single or a few two dimensional (2D) measurements. Binary random coded apertures with square pixels are primarily implemented in CASSI systems to modulate the spectral images in spatial domain. The design and optimization of coded apertures was shown to improve the imaging performance of these systems significantly. This work proposes a different approach to code design. Instead of traditional squared tiled coded elements, hexagonal tiled elements are used. The dislocation between the binary hexagonal pixels on coded apertures and the square pixels on detector introduces equivalent grey-scale spatial modulation to increase the degrees of freedom in the sensing matrix, thus further improving the spectral imaging performance. Then, this paper…
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