Sub-nyquist sampling strategy for compressive single-pixel imaging

Singe-Pixel Imaging (SPI) captures image using only a single-pixel detector instead of pixelated sensors sensor. It has been a cost-effective alternative to conventional camera especially in non-visible wavelengths and low light conditions. Generally, SPI works with compressive sensing (CS) to achie...

Full description

Bibliographic Details
Main Author: Chin, Vui Nam
Format: Final Year Project / Dissertation / Thesis
Published: 2022
Subjects:
Online Access:http://eprints.utar.edu.my/4965/
http://eprints.utar.edu.my/4965/1/3E_1701944_FYP_report_%2D_VUI_NAM_CHIN.pdf
_version_ 1848886289766547456
author Chin, Vui Nam
author_facet Chin, Vui Nam
author_sort Chin, Vui Nam
building UTAR Institutional Repository
collection Online Access
description Singe-Pixel Imaging (SPI) captures image using only a single-pixel detector instead of pixelated sensors sensor. It has been a cost-effective alternative to conventional camera especially in non-visible wavelengths and low light conditions. Generally, SPI works with compressive sensing (CS) to achieve sub-Nyquist sampling where efficiency can be increased significantly. Nevertheless, image quality remains a primary concern of SPI. Therefore, this project is aimed to propose an adaptive sampling scheme to improve image quality and efficiency in compressive SPI. Coarse-to-fine (CTF) is able to improve the image quality by sampling the scene progressively from low to high resolution. In this project, in-depth investigation was performed on CTF, particularly to analyse the performance of various step size strategies and progressive reconstruction. Additionally, 1-bit CS was also explored for its potential in performance improvement. Results show that the performance of decreasing step size is better than fixed step size in CTF. Furthermore, outline enhancement is proposed by integrating CTF sampling and 1-bit CS. Based on the results, outline enhancement is able to improve the image quality in SPI especially when the modified sampling patterns is 5 % of total sampling patterns. In conclusion, this project has proposed two sampling methods: decreasing step size as adaptive step size strategy for CTF sampling and outline enhancement scheme to improve the overall image quality in compressive SPI.
first_indexed 2025-11-15T19:36:08Z
format Final Year Project / Dissertation / Thesis
id utar-4965
institution Universiti Tunku Abdul Rahman
institution_category Local University
last_indexed 2025-11-15T19:36:08Z
publishDate 2022
recordtype eprints
repository_type Digital Repository
spelling utar-49652022-12-23T13:26:15Z Sub-nyquist sampling strategy for compressive single-pixel imaging Chin, Vui Nam TK Electrical engineering. Electronics Nuclear engineering Singe-Pixel Imaging (SPI) captures image using only a single-pixel detector instead of pixelated sensors sensor. It has been a cost-effective alternative to conventional camera especially in non-visible wavelengths and low light conditions. Generally, SPI works with compressive sensing (CS) to achieve sub-Nyquist sampling where efficiency can be increased significantly. Nevertheless, image quality remains a primary concern of SPI. Therefore, this project is aimed to propose an adaptive sampling scheme to improve image quality and efficiency in compressive SPI. Coarse-to-fine (CTF) is able to improve the image quality by sampling the scene progressively from low to high resolution. In this project, in-depth investigation was performed on CTF, particularly to analyse the performance of various step size strategies and progressive reconstruction. Additionally, 1-bit CS was also explored for its potential in performance improvement. Results show that the performance of decreasing step size is better than fixed step size in CTF. Furthermore, outline enhancement is proposed by integrating CTF sampling and 1-bit CS. Based on the results, outline enhancement is able to improve the image quality in SPI especially when the modified sampling patterns is 5 % of total sampling patterns. In conclusion, this project has proposed two sampling methods: decreasing step size as adaptive step size strategy for CTF sampling and outline enhancement scheme to improve the overall image quality in compressive SPI. 2022 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/4965/1/3E_1701944_FYP_report_%2D_VUI_NAM_CHIN.pdf Chin, Vui Nam (2022) Sub-nyquist sampling strategy for compressive single-pixel imaging. Final Year Project, UTAR. http://eprints.utar.edu.my/4965/
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Chin, Vui Nam
Sub-nyquist sampling strategy for compressive single-pixel imaging
title Sub-nyquist sampling strategy for compressive single-pixel imaging
title_full Sub-nyquist sampling strategy for compressive single-pixel imaging
title_fullStr Sub-nyquist sampling strategy for compressive single-pixel imaging
title_full_unstemmed Sub-nyquist sampling strategy for compressive single-pixel imaging
title_short Sub-nyquist sampling strategy for compressive single-pixel imaging
title_sort sub-nyquist sampling strategy for compressive single-pixel imaging
topic TK Electrical engineering. Electronics Nuclear engineering
url http://eprints.utar.edu.my/4965/
http://eprints.utar.edu.my/4965/1/3E_1701944_FYP_report_%2D_VUI_NAM_CHIN.pdf