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laplacian of gaussian (log) filter  (MathWorks Inc)


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    MathWorks Inc laplacian of gaussian (log) filter
    Laplacian Of Gaussian (Log) Filter, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/laplacian of gaussian (log) filter/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    laplacian of gaussian (log) filter - by Bioz Stars, 2026-04
    90/100 stars

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    MathWorks Inc laplacian filter
    The effect of spatial filtering on MLP-NN classification accuracy. No-Filter shows the detection accuracy with no spatial filter. CAR shows the effect of re-referencing by Common Average Reference (CAR). CAR & Lap shows the effect of both re-referencing by CAR and applying the <t>Laplacian</t> filter. The standard deviations are [0.7,0.5, 0.6, 0.5,1.2,0.6] for the 1st to 6th bar, respectively. The accuracy of no-Filter dataset was significantly higher than those of CSP dataset and Laplacian dataset. The accuracy of CSP was significantly higher than Laplacian. Adding CAR did not changed the accuracies significantly.
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    The example of image processing for objectively analyzing the sharpness of an image. ( A ) The pair of original gonio-photographs. ( B ) The pair of A images after conversion to grayscale. ( C ) The pair of results after the <t>Laplacian</t> filter processing with B image (|Δ I |). The focus-stacked image exhibited more edges ( white part ) than the best-focused one visually.
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    Image Search Results


    The effect of spatial filtering on MLP-NN classification accuracy. No-Filter shows the detection accuracy with no spatial filter. CAR shows the effect of re-referencing by Common Average Reference (CAR). CAR & Lap shows the effect of both re-referencing by CAR and applying the Laplacian filter. The standard deviations are [0.7,0.5, 0.6, 0.5,1.2,0.6] for the 1st to 6th bar, respectively. The accuracy of no-Filter dataset was significantly higher than those of CSP dataset and Laplacian dataset. The accuracy of CSP was significantly higher than Laplacian. Adding CAR did not changed the accuracies significantly.

    Journal: IEEE ... International Conference on Rehabilitation Robotics : [proceedings]

    Article Title: Evaluation of Multi-layer Perceptron Neural Networks in Predicting Ankle Dorsiflexion in Healthy Adults using Movement-related Cortical Potentials for BCI-Neurofeedback Applications

    doi: 10.1109/ICORR55369.2022.9896584

    Figure Lengend Snippet: The effect of spatial filtering on MLP-NN classification accuracy. No-Filter shows the detection accuracy with no spatial filter. CAR shows the effect of re-referencing by Common Average Reference (CAR). CAR & Lap shows the effect of both re-referencing by CAR and applying the Laplacian filter. The standard deviations are [0.7,0.5, 0.6, 0.5,1.2,0.6] for the 1st to 6th bar, respectively. The accuracy of no-Filter dataset was significantly higher than those of CSP dataset and Laplacian dataset. The accuracy of CSP was significantly higher than Laplacian. Adding CAR did not changed the accuracies significantly.

    Article Snippet: Laplacian filter was applied using Current Source Density (CSD) toolbox version 1.1 in MATLAB.

    Techniques:

    True positive rates (TPR) and false rates (FPR).

    Journal: IEEE ... International Conference on Rehabilitation Robotics : [proceedings]

    Article Title: Evaluation of Multi-layer Perceptron Neural Networks in Predicting Ankle Dorsiflexion in Healthy Adults using Movement-related Cortical Potentials for BCI-Neurofeedback Applications

    doi: 10.1109/ICORR55369.2022.9896584

    Figure Lengend Snippet: True positive rates (TPR) and false rates (FPR).

    Article Snippet: Laplacian filter was applied using Current Source Density (CSD) toolbox version 1.1 in MATLAB.

    Techniques:

    The example of image processing for objectively analyzing the sharpness of an image. ( A ) The pair of original gonio-photographs. ( B ) The pair of A images after conversion to grayscale. ( C ) The pair of results after the Laplacian filter processing with B image (|Δ I |). The focus-stacked image exhibited more edges ( white part ) than the best-focused one visually.

    Journal: Translational Vision Science & Technology

    Article Title: Automated Focal Plane Merging From a Stack of Gonioscopic Photographs Using a Focus-Stacking Algorithm

    doi: 10.1167/tvst.11.4.22

    Figure Lengend Snippet: The example of image processing for objectively analyzing the sharpness of an image. ( A ) The pair of original gonio-photographs. ( B ) The pair of A images after conversion to grayscale. ( C ) The pair of results after the Laplacian filter processing with B image (|Δ I |). The focus-stacked image exhibited more edges ( white part ) than the best-focused one visually.

    Article Snippet: The energy of the Laplacian, which is a measure of image sharpness was analyzed with the Laplacian filter (Nidek Co., Gamagori, Japan) and compared for each set.

    Techniques:

    Comparisons Between the Assessments for the Gonio-Photos With and Without the Focus-Stacking Processing

    Journal: Translational Vision Science & Technology

    Article Title: Automated Focal Plane Merging From a Stack of Gonioscopic Photographs Using a Focus-Stacking Algorithm

    doi: 10.1167/tvst.11.4.22

    Figure Lengend Snippet: Comparisons Between the Assessments for the Gonio-Photos With and Without the Focus-Stacking Processing

    Article Snippet: The energy of the Laplacian, which is a measure of image sharpness was analyzed with the Laplacian filter (Nidek Co., Gamagori, Japan) and compared for each set.

    Techniques:

    The representative pairs of focus-stacked and best-focused images, in which the focal plane merging technique achieved the significant deepening of the depth of field and improvement of informativeness and increased energy of the Laplacian. The salient areas of interest are indicated by white arrows . ( A ) The images show tall tent-shaped peripheral anterior synechiae (PAS). The focus-stacked image has clearer PAS boundaries and more detail about iris damage. ( B ) The pair of images is an example of pseudoexfoliation glaucoma. The shape and shade of angle pigmentation can be observed in the focus-stacked image compared with the best-focused one. ( C ) The pair of images is an example after trabeculectomy. Compared with the best-focused image, the focus-stacked image clearly shows the peripheral iridectomy scar and iris damage. ( D ) As an example, after the EX-PRESS Glaucoma Filtration Device (Alcon Laboratories, Fort Worth, TX) procedure, the DOF in the focus-stacked image is deep enough to be observed the angle from the tip of the device to the insertion area compared with that of the best-focused one. ( E ) The pair of images is an example after the Ahmed glaucoma valve implantation (Model FP-7; New World Medical, Rancho Cucamonga, CA) into the anterior chamber. Compared with the best-focused image, the focus-stacked one has a wider range of focus, and it can be observed well from the tip of the device to the insertion part. Moreover, its lumen can be seen.

    Journal: Translational Vision Science & Technology

    Article Title: Automated Focal Plane Merging From a Stack of Gonioscopic Photographs Using a Focus-Stacking Algorithm

    doi: 10.1167/tvst.11.4.22

    Figure Lengend Snippet: The representative pairs of focus-stacked and best-focused images, in which the focal plane merging technique achieved the significant deepening of the depth of field and improvement of informativeness and increased energy of the Laplacian. The salient areas of interest are indicated by white arrows . ( A ) The images show tall tent-shaped peripheral anterior synechiae (PAS). The focus-stacked image has clearer PAS boundaries and more detail about iris damage. ( B ) The pair of images is an example of pseudoexfoliation glaucoma. The shape and shade of angle pigmentation can be observed in the focus-stacked image compared with the best-focused one. ( C ) The pair of images is an example after trabeculectomy. Compared with the best-focused image, the focus-stacked image clearly shows the peripheral iridectomy scar and iris damage. ( D ) As an example, after the EX-PRESS Glaucoma Filtration Device (Alcon Laboratories, Fort Worth, TX) procedure, the DOF in the focus-stacked image is deep enough to be observed the angle from the tip of the device to the insertion area compared with that of the best-focused one. ( E ) The pair of images is an example after the Ahmed glaucoma valve implantation (Model FP-7; New World Medical, Rancho Cucamonga, CA) into the anterior chamber. Compared with the best-focused image, the focus-stacked one has a wider range of focus, and it can be observed well from the tip of the device to the insertion part. Moreover, its lumen can be seen.

    Article Snippet: The energy of the Laplacian, which is a measure of image sharpness was analyzed with the Laplacian filter (Nidek Co., Gamagori, Japan) and compared for each set.

    Techniques: Filtration