information filters Search Results


filter and amplifier (ultravox 4-channel system)  (Noldus Information Technology)
90
Noldus Information Technology filter and amplifier (ultravox 4-channel system)
Filter And Amplifier (Ultravox 4 Channel System), supplied by Noldus Information Technology, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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10-channel nif filter-fluorescer x-ray (fflex) diagnostic  (Neuroscience Information Framework)
90
Neuroscience Information Framework 10-channel nif filter-fluorescer x-ray (fflex) diagnostic
10 Channel Nif Filter Fluorescer X Ray (Fflex) Diagnostic, supplied by Neuroscience Information Framework, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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aggregate (filtered) from national center for biotechnology information mus musculus annotation release 106  (Biotechnology Information)
90
Biotechnology Information aggregate (filtered) from national center for biotechnology information mus musculus annotation release 106
Aggregate (Filtered) From National Center For Biotechnology Information Mus Musculus Annotation Release 106, supplied by Biotechnology Information, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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uv filter  (Biotechnology Information)
90
Biotechnology Information uv filter
Uv Filter, supplied by Biotechnology Information, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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filter fluorescer fflex diagnostic  (Neuroscience Information Framework)
90
Neuroscience Information Framework filter fluorescer fflex diagnostic
Filter Fluorescer Fflex Diagnostic, supplied by Neuroscience Information Framework, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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naïve inverse filter  (Neuroscience Information Framework)
90
Neuroscience Information Framework naïve inverse filter
Orthogonal sections of the maximum intensity projection (MIP) of a degraded 3D synthetic volume after deconvolution using various algorithms. From top left to bottom right: ground-truth volume, degraded volume (after convolution with PSF and simulate noise), <t>naïve</t> inverse <t>filter</t> <t>(NIF),</t> regularized inverse Filter (RIF), Tikhonov regularization (TR), Landweber iteration (LW), Richardson–Lucy (RL), Tikhonov–Miller (TM), Fast Iterative Shrinkage-Thresholding Algorithm (FISTA, l 1 minimization), and Richardson–Lucy with total variation (RL-TV). A non-negativity constraint was used for all algorithms. The setting of the optimal parameters for each deconvolution algorithm was performed through visual assessment. Reprinted from with permission from ref . Copyright 2017 Elsevier.
Naïve Inverse Filter, supplied by Neuroscience Information Framework, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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pore size filters  (Biotechnology Information)
90
Biotechnology Information pore size filters
Orthogonal sections of the maximum intensity projection (MIP) of a degraded 3D synthetic volume after deconvolution using various algorithms. From top left to bottom right: ground-truth volume, degraded volume (after convolution with PSF and simulate noise), <t>naïve</t> inverse <t>filter</t> <t>(NIF),</t> regularized inverse Filter (RIF), Tikhonov regularization (TR), Landweber iteration (LW), Richardson–Lucy (RL), Tikhonov–Miller (TM), Fast Iterative Shrinkage-Thresholding Algorithm (FISTA, l 1 minimization), and Richardson–Lucy with total variation (RL-TV). A non-negativity constraint was used for all algorithms. The setting of the optimal parameters for each deconvolution algorithm was performed through visual assessment. Reprinted from with permission from ref . Copyright 2017 Elsevier.
Pore Size Filters, supplied by Biotechnology Information, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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ultrasound detector, filter and amplifier  (Noldus Information Technology)
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Noldus Information Technology ultrasound detector, filter and amplifier
Orthogonal sections of the maximum intensity projection (MIP) of a degraded 3D synthetic volume after deconvolution using various algorithms. From top left to bottom right: ground-truth volume, degraded volume (after convolution with PSF and simulate noise), <t>naïve</t> inverse <t>filter</t> <t>(NIF),</t> regularized inverse Filter (RIF), Tikhonov regularization (TR), Landweber iteration (LW), Richardson–Lucy (RL), Tikhonov–Miller (TM), Fast Iterative Shrinkage-Thresholding Algorithm (FISTA, l 1 minimization), and Richardson–Lucy with total variation (RL-TV). A non-negativity constraint was used for all algorithms. The setting of the optimal parameters for each deconvolution algorithm was performed through visual assessment. Reprinted from with permission from ref . Copyright 2017 Elsevier.
Ultrasound Detector, Filter And Amplifier, supplied by Noldus Information Technology, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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bloom filters  (Biotechnology Information)
90
Biotechnology Information bloom filters
Orthogonal sections of the maximum intensity projection (MIP) of a degraded 3D synthetic volume after deconvolution using various algorithms. From top left to bottom right: ground-truth volume, degraded volume (after convolution with PSF and simulate noise), <t>naïve</t> inverse <t>filter</t> <t>(NIF),</t> regularized inverse Filter (RIF), Tikhonov regularization (TR), Landweber iteration (LW), Richardson–Lucy (RL), Tikhonov–Miller (TM), Fast Iterative Shrinkage-Thresholding Algorithm (FISTA, l 1 minimization), and Richardson–Lucy with total variation (RL-TV). A non-negativity constraint was used for all algorithms. The setting of the optimal parameters for each deconvolution algorithm was performed through visual assessment. Reprinted from with permission from ref . Copyright 2017 Elsevier.
Bloom Filters, supplied by Biotechnology Information, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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information filters  (EcoDesign Inc)
90
EcoDesign Inc information filters
Orthogonal sections of the maximum intensity projection (MIP) of a degraded 3D synthetic volume after deconvolution using various algorithms. From top left to bottom right: ground-truth volume, degraded volume (after convolution with PSF and simulate noise), <t>naïve</t> inverse <t>filter</t> <t>(NIF),</t> regularized inverse Filter (RIF), Tikhonov regularization (TR), Landweber iteration (LW), Richardson–Lucy (RL), Tikhonov–Miller (TM), Fast Iterative Shrinkage-Thresholding Algorithm (FISTA, l 1 minimization), and Richardson–Lucy with total variation (RL-TV). A non-negativity constraint was used for all algorithms. The setting of the optimal parameters for each deconvolution algorithm was performed through visual assessment. Reprinted from with permission from ref . Copyright 2017 Elsevier.
Information Filters, supplied by EcoDesign Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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filter's transformation of chromatic information  (LAGeT LLC)
90
LAGeT LLC filter's transformation of chromatic information
Orthogonal sections of the maximum intensity projection (MIP) of a degraded 3D synthetic volume after deconvolution using various algorithms. From top left to bottom right: ground-truth volume, degraded volume (after convolution with PSF and simulate noise), <t>naïve</t> inverse <t>filter</t> <t>(NIF),</t> regularized inverse Filter (RIF), Tikhonov regularization (TR), Landweber iteration (LW), Richardson–Lucy (RL), Tikhonov–Miller (TM), Fast Iterative Shrinkage-Thresholding Algorithm (FISTA, l 1 minimization), and Richardson–Lucy with total variation (RL-TV). A non-negativity constraint was used for all algorithms. The setting of the optimal parameters for each deconvolution algorithm was performed through visual assessment. Reprinted from with permission from ref . Copyright 2017 Elsevier.
Filter's Transformation Of Chromatic Information, supplied by LAGeT LLC, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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nonlinear information filter  (Neuroscience Information Framework)
90
Neuroscience Information Framework nonlinear information filter
Orthogonal sections of the maximum intensity projection (MIP) of a degraded 3D synthetic volume after deconvolution using various algorithms. From top left to bottom right: ground-truth volume, degraded volume (after convolution with PSF and simulate noise), <t>naïve</t> inverse <t>filter</t> <t>(NIF),</t> regularized inverse Filter (RIF), Tikhonov regularization (TR), Landweber iteration (LW), Richardson–Lucy (RL), Tikhonov–Miller (TM), Fast Iterative Shrinkage-Thresholding Algorithm (FISTA, l 1 minimization), and Richardson–Lucy with total variation (RL-TV). A non-negativity constraint was used for all algorithms. The setting of the optimal parameters for each deconvolution algorithm was performed through visual assessment. Reprinted from with permission from ref . Copyright 2017 Elsevier.
Nonlinear Information Filter, supplied by Neuroscience Information Framework, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


Orthogonal sections of the maximum intensity projection (MIP) of a degraded 3D synthetic volume after deconvolution using various algorithms. From top left to bottom right: ground-truth volume, degraded volume (after convolution with PSF and simulate noise), naïve inverse filter (NIF), regularized inverse Filter (RIF), Tikhonov regularization (TR), Landweber iteration (LW), Richardson–Lucy (RL), Tikhonov–Miller (TM), Fast Iterative Shrinkage-Thresholding Algorithm (FISTA, l 1 minimization), and Richardson–Lucy with total variation (RL-TV). A non-negativity constraint was used for all algorithms. The setting of the optimal parameters for each deconvolution algorithm was performed through visual assessment. Reprinted from with permission from ref . Copyright 2017 Elsevier.

Journal: Analytical Chemistry

Article Title: Computational Super-Resolution: An Odyssey in Harnessing Priors to Enhance Optical Microscopy Resolution

doi: 10.1021/acs.analchem.4c07047

Figure Lengend Snippet: Orthogonal sections of the maximum intensity projection (MIP) of a degraded 3D synthetic volume after deconvolution using various algorithms. From top left to bottom right: ground-truth volume, degraded volume (after convolution with PSF and simulate noise), naïve inverse filter (NIF), regularized inverse Filter (RIF), Tikhonov regularization (TR), Landweber iteration (LW), Richardson–Lucy (RL), Tikhonov–Miller (TM), Fast Iterative Shrinkage-Thresholding Algorithm (FISTA, l 1 minimization), and Richardson–Lucy with total variation (RL-TV). A non-negativity constraint was used for all algorithms. The setting of the optimal parameters for each deconvolution algorithm was performed through visual assessment. Reprinted from with permission from ref . Copyright 2017 Elsevier.

Article Snippet: The performance of the naïve inverse filter is shown in Figure (NIF), where the result is full of noise.

Techniques: