{"id":"W2059440857","doi":"10.1117/12.2053551","title":"Image quality assessment of 2-chip color camera in comparison with 1-chip color and 3-chip color cameras in various lighting conditions: initial results","year":2014,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Image Fusion Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Atlantic Canada Opportunities Agency","keywords":"Panchromatic film; Computer vision; Artificial intelligence; Color image; Computer science; Monochrome; Camera auto-calibration; Image sensor; Camera module; Smart camera; Multispectral image; Chip; Image resolution; Three-CCD camera; Color histogram; False color; RGB color model; Demosaicing; Image processing; Camera resectioning; Image (mathematics); Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008512099,0.0005385333,0.0004688225,0.0008556997,0.000220956,0.0005225301,0.0002961245,0.0005257793,0.001047332],"category_scores_gemma":[0.001397202,0.000199621,0.0004575051,0.0005465061,0.0003219404,0.0007748407,0.0004160364,0.0003148531,0.000188715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003789139,"about_ca_system_score_gemma":0.0001956607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001761823,"about_ca_topic_score_gemma":0.001864522,"domain_scores_codex":[0.999126,0.0001333558,0.00002819067,0.0001365135,0.0005023328,0.00007351216],"domain_scores_gemma":[0.9983121,0.0002455525,0.0001597598,0.0001156175,0.001080194,0.00008681818],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001208111,0.0002391767,0.01353148,0.0006941061,0.0001269249,0.0003580227,0.0003904161,0.00627562,0.869565,0.0003590806,0.0005429444,0.1067091],"study_design_scores_gemma":[0.00006224379,0.004314441,0.08123727,0.00005453629,0.0002374567,0.001356797,0.0005533037,0.04261452,0.8657452,0.0001649057,0.003518313,0.0001410264],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9107398,0.004429335,0.08065281,0.00009164272,0.00008752036,0.0001718041,0.0001959919,0.000374839,0.003256171],"genre_scores_gemma":[0.9456515,0.001921783,0.04939809,0.00007911128,0.00003475282,0.00006059514,0.0002816315,0.00007597,0.002496513],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001761823,"threshold_uncertainty_score":0.0045017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01481960007701022,"score_gpt":0.2916400442656094,"score_spread":0.2768204441885992,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}