The structure of the eyes in the Previous Digital Image Processing Reading Notes has already described the basic structure and brightness adaptability level of the eyes. The brightness discrimination (brightness discrimination) is now a more detailed summary.
Several basic definitions, refer:
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Reflection SurfaceIt is composed of the physical boundaries of two materials with different refractive indexes, such as air and the interface of the tissue.
ReflectionThe return of electromagnetic radiation on the incident surface is defined as follows:It has mirror reflection and diffuse reflection.
Diffuse ReflectionIt is a common phenomenon of biological tissue because they do not have a polished surface like an optical reflection surface.
Weber bi(Weber ratio) is used to express the brightness discrimination capability. The formula is: △ic/I. This has something to do with an experiment. A large diffuse reflection that occupies the full field of view of the observer (possibly glass) is illuminated by the intensity I light. Then increase the light intensity, and the added part is represented by the variable △i. When the observer detects the brightness change, take 50% of the value, and use the variable Delta IC to represent it and calculate the Delta IC/I value. The smaller the value, the better the brightness discrimination ability of the observer. On the contrary, this observer's eyes are not good.
As mentioned above, the logarithm can be used as an amplifier. The X and Y axes of the following charts are enlarged by logarithm.
It can be seen that Weber is relatively large when the objective brightness is relatively small, so the brightness of the human eye at this time is poor.
With ObjectiveBrightnessIncrease, the Weber ratio is smaller, and the human eye brightness identification capability is enhanced.
However, simple functions do not fully explain the brightness discrimination capability.
Tape(Mach bands) describes the visual uplink and downlink dashboard.
Comparison(Simultaneous contrast) explains that the brightness of an object observed on different backgrounds is different.
In addition, the"Illusion(Optical regression sion ).