{"id":"W2040661103","doi":"10.1117/12.2053554","title":"Influence of image compression on the quality of UNB pan-sharpened imagery: a case study with security video image frames","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":"","keywords":"Computer vision; Panchromatic film; Artificial intelligence; Computer science; Color image; Monochrome; Image resolution; Sub-pixel resolution; False color; Multispectral image; Image quality; Image processing; Digital image processing; Image (mathematics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001257005,0.0004287836,0.0007062555,0.0001240362,0.00008979211,0.0000703027,0.001031172,0.0001504226,0.00001122958],"category_scores_gemma":[0.001373976,0.0002941083,0.0003971703,0.0004222396,0.0004986883,0.000756847,0.0002543834,0.0005328622,7.266414e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001028432,"about_ca_system_score_gemma":0.00002004904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006148908,"about_ca_topic_score_gemma":7.997815e-7,"domain_scores_codex":[0.997245,1.79653e-7,0.001071161,0.0003958817,0.0009294834,0.000358311],"domain_scores_gemma":[0.9962624,0.0006286796,0.0006375263,0.0001813545,0.002193318,0.00009676899],"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":[0.0002009543,0.0003294804,0.0005929,0.001076385,0.0003201343,9.586871e-7,0.0007903577,0.0008833744,0.9537205,0.04113283,0.0007103647,0.0002417339],"study_design_scores_gemma":[0.001415348,0.001059244,0.002829307,0.0008673051,0.0001492385,0.00004595771,0.004551199,0.03489336,0.9512298,0.002290577,0.0001607903,0.0005078624],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967051,0.00003258154,0.0006381502,0.0003320329,0.00004793445,0.001101173,0.00008045276,0.0002067021,0.000855915],"genre_scores_gemma":[0.9231359,0.00003358162,0.07644463,0.0000405532,0.00007341317,0.0001843755,0.00000294151,0.00007326416,0.00001127371],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07580648,"threshold_uncertainty_score":0.9999511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01030980728692399,"score_gpt":0.2631996483019799,"score_spread":0.2528898410150559,"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."}}