= NIH Image
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<NIH Image> is <Wayne Rasband>'s historical image-processing program for the <Macintosh>, preceding <ImageJ>. Its official documentation describes image acquisition, editing, filtering, calibrated measurements, stacks, a macro language and plug-in extensions.<Wayne Rasband profile on ImageJ.net>[Image/NIH Image/ImageJ software history]{ref}<NIH Image documentation>[About NIH Image; manual Introduction and Overview]{ref}
One concrete representation choice explains why software history matters for interpreting old results. The manual describes internal pixels as unsigned 8-bit values and import of 16-bit data by rescaling to 8 bits. It also documents the convention of displaying value 0 as white and 255 as black; screen appearance and stored numerical values are distinct.<NIH Image documentation>[Manual Introduction, Overview, Images]{ref}
For an original chosen conversion model, suppose a high-bit-depth image uses values from 0 to 4095 and is mapped to 8 bits by
$$
Q(v)=\left\lfloor\frac{255v}{4095}+\frac12\right\rfloor.
$$
Then $Q(1000)=Q(1001)=62$. Two distinct recorded values become identical, so no subsequent measurement of the converted image can recover their difference. This is a stated <quantization (signal processing)> model, not an assertion about an undocumented rounding detail in NIH Image.
Keep the original data and the scaling rule when comparing legacy measurements. Spatial calibration is a separate operation: changing a length-per-pixel setting does not restore discarded gray-value information. The manual's analysis workflow selects a <region of interest>, computes measurements and records results, making those representation and selection choices part of a reproducible calculation.<NIH Image documentation>[Making Measurements; spatial Set Scale versus density Calibrate]{ref}
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