Hamamatsu Corporation

Deconvolution Deblur (DNN-D) deblurs images based on algorithms of no neighbor and nearest neighbor to complement SimplePCI and remove haze from optical image sections. Out-of-focus haze is mathematically modeled from a Point-Spread Function (PSF) to deblur an image. DNN-D supports nearest neighbor and no neighbor for rapid deblurring of an image or sequence.

DNN-D Features:

Based on established algorithms from AutoQuant Imaging, Inc.

Remove blur from images using fast algorithms

Apply to individual images or image sequences automatically

Deblur multi-wavelength images

Automatic PSF generation

Apply to full image or image region for fast parameter tuning

Deconvolution 2D Blind (DNN-2D)

Deconvolution 2D Blind (DNN-2D) combines restorative deconvolution algorithms and positions SimplePCI to identify out-of-focus haze and restore it to its original point. A PSF is automatically derived from an image and used in restoration. In addition, DNN-2D is supplied with nearest neighbor and no neighbor algorithms.

DNN-2D Features:

Based on established algorithms from AutoQuant Imaging, Inc.

Process an individual image or image sequence

Works with widefield, brightfield and confocal images

Automatic PSF determination

Ideal for time-lapse imaging

Automatically process sequences of 2D images

Monochrome or multi-color fluorescence images

Applications:

Biological or materials images

Enhance detail for 3D reconstruction

Image processing

Brightfield microscopy

Widefield microscopy

Confocal microscopy

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Deconvolution (DNN)

Deconvolution 2D Blind (DNN-2D)