{"id":"W2108255549","doi":"10.1109/mwscas.2008.4616783","title":"Improved image restoration using wavelet-based denoising and fourier-based deconvolution","year":2008,"lang":"en","type":"article","venue":"","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Blind deconvolution; Deconvolution; Circulant matrix; Image restoration; Wavelet; Algorithm; Artificial intelligence; Mathematics; Discrete wavelet transform; Computer science; Wiener deconvolution; Noise reduction; Discrete Fourier transform (general); Wavelet transform; Fourier transform; Pattern recognition (psychology); Image (mathematics); Short-time Fourier transform; Image processing; Fourier analysis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009631899,0.00067681,0.00100139,0.0009647626,0.000265064,0.000525405,0.0007306708,0.001020472,0.00089219],"category_scores_gemma":[0.002131145,0.0003215337,0.001001025,0.0008661787,0.0007214666,0.001324373,0.0009236024,0.0007855824,0.0004906541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002722403,"about_ca_system_score_gemma":0.0005532161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007483802,"about_ca_topic_score_gemma":0.00102803,"domain_scores_codex":[0.9995145,0.00009990111,0.00003004402,0.0001034884,0.0002222126,0.00002990892],"domain_scores_gemma":[0.9994924,0.000153843,0.00007382117,0.00008722633,0.0001747605,0.00001780438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002810363,0.0001537331,0.001088866,0.0005413512,0.000146147,0.0003846001,0.0002754851,0.1432197,0.3953307,0.02721575,0.001909383,0.4294533],"study_design_scores_gemma":[0.00002117517,0.00008982585,0.0006853669,0.000018724,0.00004402376,0.0005339145,0.00002549171,0.9047186,0.08473498,0.005010968,0.004076824,0.00004016138],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00979218,0.0002915912,0.9890323,0.00006412486,0.00002620424,0.00001198659,0.000009517776,0.0001643426,0.0006077033],"genre_scores_gemma":[0.1142629,0.0008895116,0.8825988,0.00008141719,0.00005466023,0.00003639518,0.00006978787,0.0001006434,0.001905934],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001020472,"threshold_uncertainty_score":0.005093932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04200224872022293,"score_gpt":0.2845209284433669,"score_spread":0.242518679723144,"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."}}