{"doi":"10.1364/ao.479069","title":"Single-pixel imaging with high spectral and spatial resolution","abstract":"<jats:p>It has long been a challenge to obtain high spectral and spatial resolution simultaneously for the field of measurement and detection. Here we present a measurement system based on single-pixel imaging with compressive sensing that can realize excellent spectral and spatial resolution at the same time, as well as data compression. Our method can achieve high spectral and spatial resolution, which is different from the mutually restrictive relationship between the two in traditional imaging. In our experiments, 301 spectral channels are obtained in the band of 420–780 nm with a spectral resolution of 1.2 nm and a spatial resolution of 1.11 mrad. A sampling rate of 12.5% for a 64×64pixel image is obtained by using compressive sensing, which also reduces the measurement time; thus, high spectral and spatial resolution are realized simultaneously, even at a low sampling rate.</jats:p>","journal":"Applied Optics","year":2023,"id":679846,"datarank":0.3596842909197557,"base_score":2.3978952727983707,"endowment":2.3978952727983707,"self_citation_contribution":0.3596842909197557,"citation_network_contribution":0.0,"self_endowment_contribution":0.3596842909197557,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":10,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1776301,"name":"Zhaohua Yang","orcid":"0000-0002-1481-9952","position":1,"is_corresponding":false},{"id":510566,"name":"Ping Li","orcid":"0000-0001-9893-284X","position":2,"is_corresponding":false},{"id":1776305,"name":"Zidong Zhao","orcid":null,"position":3,"is_corresponding":false},{"id":320344,"name":"Ying Liu","orcid":"0000-0002-4966-3476","position":4,"is_corresponding":false},{"id":1776308,"name":"Yuanjin Yu","orcid":"0000-0003-1713-1632","position":5,"is_corresponding":false},{"id":1776310,"name":"Ling-an Wu","orcid":"0000-0002-0777-5269","position":6,"is_corresponding":false},{"id":469707,"name":"Mingyue Song","orcid":"0000-0002-6107-3532","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Single-pixel imaging with high spectral and spatial resolution","abstract":"<jats:p>It has long been a challenge to obtain high spectral and spatial resolution simultaneously for the field of measurement and detection. Here we present a measurement system based on single-pixel imaging with compressive sensing that can realize excellent spectral and spatial resolution at the same time, as well as data compression. Our method can achieve high spectral and spatial resolution, which is different from the mutually restrictive relationship between the two in traditional imaging. In our experiments, 301 spectral channels are obtained in the band of 420–780 nm with a spectral resolution of 1.2 nm and a spatial resolution of 1.11 mrad. A sampling rate of 12.5% for a 64×64pixel image is obtained by using compressive sensing, which also reduces the measurement time; thus, high spectral and spatial resolution are realized simultaneously, even at a low sampling rate.</jats:p>","is_dataset_classified":null,"base_score":2.3978952727983707,"endowment":2.3978952727983707,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"37132810","pmcid":null,"openalex_id":"https://openalex.org/W4323836127","authors":[],"funders":[{"funder_name":"National Natural Science Foundation of China","grant_id":"61973018","title":null},{"funder_name":"National Natural Science Foundation of China","grant_id":"62173039","title":null},{"funder_name":"Civil Space Project","grant_id":"D040301","title":null},{"funder_name":"Defense Industrial Technology Development Program","grant_id":"JCKY2021602B036","title":null}],"total_grants":4,"fwci":0.9504,"citation_percentile":0.67521368,"influential_citations":0,"citation_trend":[{"year":2023,"count":1},{"year":2024,"count":3},{"year":2025,"count":3},{"year":2026,"count":3}],"oa_status":"closed","license":"https://doi.org/10.1364/OA_License_v2#VOR","oa_locations":[{"url":"https://opg.optica.org/viewmedia.cfm?URI=ao-62-10-2610&seq=0","host_type":"publisher"},{"url":"https://doi.org/10.1364/ao.479069","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/37132810","host_type":"repository"}],"fields_of_study":["Random lasers and scattering media","Orbital Angular Momentum in Optics","Neural Networks and Reservoir Computing"],"mesh_terms":[],"keywords":["Image resolution","Spectral imaging","Optics","Spectral resolution","Pixel","Compressed sensing","Resolution (logic)","Full spectral imaging","Temporal resolution","Sampling (signal processing)","Hyperspectral imaging","Sub-pixel resolution","Remote sensing","Materials science","Physics","Image processing","Computer science","Spectral line","Detector","Image (mathematics)","Digital image processing","Geology","Computer vision","Artificial intelligence"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-17T13:53:54.446566Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}