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An image slicer divides a two-dimensional image into narrow strips and optically rearranges them into a long pseudo-slit. A spectrograph then disperses each strip while preserving its position along the slit.

An optical spectrum describes the distribution of optical radiation over wavelength or frequency. A spectrograph records it by separating wavelengths, while a photometric passband integrates a chosen part.

An integral field spectrograph obtains spectra throughout a two-dimensional field instead of along one slit alone. Its reduced spectral data cube is $I(x,y,\lambda )$: two coordinates locate a spatial sampling element and the third labels wavelength. One slice at fixed wavelength is an image; one column at fixed spatial position is an optical spectrum. The third axis is spectral, not a third spatial direction.

Six ways to obtain such a cube illustrate the distinction between field reformatting and scanning:

The first four are simultaneous spatially multiplexed grating arrangements. The last two deliver equivalent cube coordinates by scanning; they are imaging spectrometers rather than simultaneous grating integral-field units, and variability during the scan can corrupt the cube. Detector packing, sampling, calibration and throughput determine the practical tradeoffs.

For source counts $S$ and independent background counts $B$ with Poisson distributions, the ideal counting standard deviation is $\sqrt{S+B}$, so the signal-to-noise ratio is $S/\sqrt{S+B}$. Detector noise and uncertainty in the estimated background add further variance. A larger sky aperture raises $B$, while better throughput raises $S$; both affect the faintness limit of a spectrograph.