How does image deconvolution work?

Deconvolution is a computationally intensive image processing technique that is being increasingly utilized for improving the contrast and resolution of digital images captured in the microscope. A series of images are recorded of the sample, each shifted slightly from one another along the z-axis.

Is deconvolution possible?

Self deconvolution. However, it is also possible to use the deconvolution technique to sharpen peaks that that have no known broadening function. This is an example of “self deconvolution”, so-called because the shape of the deconvolution function is the same as the shape of the peaks in the signal.

What is blind deconvolution in image processing?

In image processing, blind deconvolution is a deconvolution technique that permits recovery of the target scene from a single or set of “blurred” images in the presence of a poorly determined or unknown point spread function (PSF). Blind deconvolution is used in astronomical imaging and medical imaging.

What is the purpose of deconvolution?

Deconvolution is a computational method that treats the image as an estimate of the true specimen intensity and using an expression for the point spread function performs the mathematical inverse of the imaging process to obtain an improved estimate of the image intensity.

What is deconvolution in signal processing?

In mathematics, deconvolution is the operation inverse to convolution. Both operations are used in signal processing and image processing. The foundations are based upon a suite of methods that are designed to remove or reverse the blurring present in microscope images induced by the limited aperture of the objective.

What is deconvolution in seismic processing?

1. n. [Geophysics] A step in seismic signal processing to recover high frequencies, attenuate multiples, equalize amplitudes, produce a zero-phase wavelet or for other purposes that generally affect the waveshape.

What is deconvolution in signals and systems?

Deconvolution is the process of filtering a signal to compensate for an undesired convolution. The goal of deconvolution is to recreate the signal as it existed before the convolution took place. This usually requires the characteristics of the convolution (i.e., the impulse or frequency response) to be known.

What is blind deconvolution in Matlab?

The blind deconvolution algorithm can be used effectively when no information about the distortion (blurring and noise) is known. The algorithm restores the image and the point-spread function (PSF) simultaneously. The accelerated, damped Richardson-Lucy algorithm is used in each iteration.

What is peak deconvolution?

“Deconvolution” is a term often applied to the process of decomposing peaks that overlap with each other, thus extracting information about the “hidden peak”. Origin provides two tools to perform peak “deconvolution”, depending upon the existence of a baseline.

What is deconvolution process?

What is spiking and predictive deconvolution?

TYPES OF DECONVOLUTION Predictive deconvolution can also be used to increase resolution by altering wavelet shape and amplitude spectrum. Spiking deconvolution is a special case where the gap is set to one sample and the resulting phase spectrum is zero.

What is non blind deconvolution?

Non-blind deconvolution is to recover the ideal image from the blurry image with the known blur kernel, while blind deconvolution is to restore the ideal image from the blurry image and the unknown blur kernel. Non-blind deconvolution is the main research in this paper.