Compressed sensing of a dichromatic color filter array
Growing interest in photography has given rise to demands for high quality images. Existing color filter array (CFA) topologies and signal sampling techniques, however, are limited. The former, which is predominantly Bayer, can at most capture 50% of the total green channel. The latter, on the other...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | text |
| Language: | English |
| Published: |
Animo Repository
2014
|
| Online Access: | https://animorepository.dlsu.edu.ph/etd_bachelors/12151 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | De La Salle University |
| Language: | English |
| Summary: | Growing interest in photography has given rise to demands for high quality images. Existing color filter array (CFA) topologies and signal sampling techniques, however, are limited. The former, which is predominantly Bayer, can at most capture 50% of the total green channel. The latter, on the other hand, is inefficient. Contemporary signal sampling techniques typically require a complete representation of the input signal. This is, subsequently, computationally expensive.
This paper proposes a new CFA topology, CY1Y2C, to theoretically extract the full green channel. However, such an approach results in an underdetermined system of linear equations, which cannot be handled by contemporary signal sampling and reconstruction methods. To address this concern, compressed sensing techniques will be used in conjunction with the proposed CFA. Said approach will involve the generation of a custom measurement matrix and recovery algorithms to yield a sparse representation of the input signal given only few measurements. |
|---|