Tag Archives: cycles per pixel

The Nikon Z7’s Insane Sharpness

Ever since getting a Nikon Z7 MILC a few months ago I have been literally blown away by the level of sharpness it produces.   I thought that my surprise might be the result of moving up from 24 to 45.7MP, or the excellent pin-point focusing mode, or the lack of an Antialiasing filter.  Well, it turns out that there is probably more at work than that.

This weekend I pulled out the largest cutter blade I could find and set it up rough and tumble near vertically about 10 meters away  to take a peek at what the MTF curves that produce such sharp results might look like.

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Taking the Sharpness Model for a Spin

The series of articles starting here outlines a model of how the various physical components of a digital camera and lens can affect the ‘sharpness’ – that is the spatial resolution – of the  images captured in the raw data.  In this one we will pit the model against MTF curves obtained through the slanted edge method[1] from real world raw captures both with and without an anti-aliasing filter.

With a few simplifying assumptions, which include ignoring aliasing and phase, the spatial frequency response (SFR or MTF) of a photographic digital imaging system near the center can be expressed as the product of the Modulation Transfer Function of each component in it.  For a current digital camera these would typically be the main ones:

(1)   \begin{equation*} MTF_{sys} = MTF_{lens} (\cdot MTF_{AA}) \cdot MTF_{pixel} \end{equation*}

all in two dimensions Continue reading Taking the Sharpness Model for a Spin

The Units of Discrete Fourier Transforms

This article is about specifying the units of the Discrete Fourier Transform of an image and the various ways that they can be expressed.  This apparently simple task can be fiendishly unintuitive.

The image we will use as an example is the familiar Airy Disk from the last few posts, at f/16 with light of mean 530nm wavelength. Zoomed in to the left in Figure 1; and as it looks in its 1024×1024 sample image to the right:

Airy Mesh and Intensity
Figure 1. Airy disc image I(x,y). Left, 1a, 3D representation, zoomed in. Right, 1b, as it would appear on the sensing plane (yes, the rings are there but you need to squint to see them).

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