23 Human wavelength encoding
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Last updated: November 24, 2025
The material about human vision in this chapter is under development, and the text is not ready to be reviewed.
Please refer to the chapters in Foundations of Vision.
23.1 Human wavelength encoding overview
When you design a digital camera, how good does it need to be? The answer depends on who you’re designing it for. If the images are for a human to look at, then the camera’s design must be guided by the capabilities and limits of the human eye. This simple principle has profound consequences for engineering.
Vision scientists have learned a great deal about the first stages of vision. We have excellent measurements of how the eye’s optics (the cornea and lens) transform light from the world into an image on the retina, and we know how the retina’s photoreceptors encode that image into neural signals. This knowledge is not just academic; it’s a practical guide for designing any system that reproduces images for people.
Consider color. A camera designed for human viewing should capture the same portion of the electromagnetic spectrum that we see: visible light. Capturing less of the spectrum would lead to poor color reproduction. Capturing more—like infrared or ultraviolet—would be wasteful, consuming resources to record information we can’t see anyway. In this sense, human wavelength sensitivity sets a clear target for camera design.
Spatial resolution presents a different challenge. It would be a disappointment if a camera failed to capture details as fine as those the human eye can resolve. We expect our photos to be at least as sharp as what we see. However, unlike with color, people are often pleased if a camera captures a scene at a finer resolution than the eye can perceive. We can always zoom in on the digital image to see details we might have missed. This extra information doesn’t interfere with the viewing experience; it just requires more storage and processing power.
So, we have two different engineering constraints derived from human vision:
- Wavelength: Human vision sets a target range. Capturing more is wasteful.
- Spatial Resolution: Human vision sets a minimum bar. Capturing more can be beneficial.
In this section, we will review the key properties of the eye that define these limits. The way our visual system samples space and encodes wavelength creates fundamental bottlenecks on what we can perceive. Understanding these limits doesn’t explain everything about what we see, but it tells us what we cannot see—essential knowledge for the field of image systems engineering.
23.2 Wavelength sampling - Thomas Young
23.3 Color matching principles - Maxwell
James Clerk Maxwell’s color matching experiments Color representations: XYZ, luminance, chromaticity, cones
23.4 Photoreceptor wavelength encoding - Thomas Young
23.4.1 Color-matching
23.4.2 Human chromatic aberrations
fise_human* script exists.
Wavelength dependence (chromatic aberration)
23.5 Retinal prostheses
Now that we know so much about the retinal encoding, the Palanker project would fit well.
THe Chichilnisky project gets thrown in at the end as next generation. Palanker fits well with the cones going forward. The Chichilnisky project fits well with motivating why we want to know what the retinal circuitry does so we address diseases when the bipolar cells (inner nuclear layer) are damaged.