![]() ![]() The image below is a single slice taken from a stack before and after deconvolution using these plugins. feature size in your sample image z-stack. The Iterative Deconvolution 3D plugin uses a PSF image z-stack to correct the image contrast vs. Alternatively, an empirical, measured PSF could be used. The Diffraction-PSF-3D plugin generates a z-stack of the theoretical point-spread function (PSF). Two plugins from Bob Dougherty can be used together to perform this systematic error correction in a 2D or 3D image. ![]() It’s the same as zeroing a scale before weighing something. If we don’t correct this systematic error, the results of the image intensity analysis could be very much more wrong than if we correct the images before analysis. Image contrast restoration by deconvolution is an important systematic error correction step for quantitative measurement of image pixel intensities in analysis workflows. We try to reverse the effects of blur in the recorded image, caused by convolution (blur, smearing, loss of contrast of small features) of the real image due to the imaging point spread function (PSF). Image contrast restoration by deconvolution is a way to correct the systematic error of contrast loss in an image recording system, such as a microscope objective lens or telescope mirror or lens. Since it’s possible to correct such a systematic error, we should! If we can measure the PSF, or guess it, we can correct the raw image for it. This is a systematic error, characterized by the Point Spread Function (PSF) of the optical system, which makes the image intensity information non-quantitative. Large features are bright, but small features appear less contrasted and dimmer than they should. The problem, and the solutionĪny optical image forming system, such as a microscope objective lens, has the nasty property of killing more and more contrast of smaller and smaller features, up to the resolution (diffraction) limit, after which there is no contrast (and thus no resolution). Deconvolution corrects the systematic error of blur (loss of contrast in smaller features) in optical systems such as fluorescence microscopy images. ![]()
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