Gamma encoding is still useful today, not just as a CRT leftover.

Its main practical purpose is to store and transmit image data in a way that better matches human vision. Our eyes are more sensitive to small differences in dark tones than in bright tones, so a gamma-like curve allocates code values more efficiently: more precision where we notice it most, with fewer bits wasted where we notice less. In that sense, gamma is a kind of perceptual compression.

That is why photographic images often start as linear sensor data but are converted to gamma-encoded spaces like sRGB for normal image files and display. With limited bit depth such as 8 bits per channel, gamma encoding gives smoother-looking tonal gradations than linear encoding would.

Historically, CRT behavior and signal standards were related to this, but the key idea is broader: the nonlinearity was actually useful because it was close to the inverse of human lightness perception. Modern displays may not be CRTs, but image standards still use gamma-encoded spaces because they remain efficient and visually appropriate.

So gamma is not only about correcting a flawed display; it is also about perceptual efficiency in image encoding and display workflows.