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A human visual system model (HVS model) is used by image processing, video processing and computer vision experts to deal with biological and psychological processes that are not yet fully understood. Such a model is used to simplify the behaviours of what is a very complex system. As our knowledge of the true visual system improves, the model is updated.
Psychovisual involves the study of the psychology of vision.
It is common to think of "taking advantage" of the HVS model to produce desired effects. Examples of taking advantage of an HVS model include colour television. Originally it was thought that colour television required too high a bandwidth for the then available technology. Then it was noticed that the colour resolution of the HVS was much lower than the brightness resolution; this allowed colour to be squeezed into the signal by chroma subsampling. Another example is image compression, like JPEG. Our HVS model says that we cannot see high frequency detail so in JPEG we can quantise these components without a perceptible loss of quality. Similar concepts are applied in audio compression, where sound frequencies inaudible to humans are bandstop filtered.
Several HVS features are derived from evolution, when we needed to defend ourselves or hunt for food. We often see demonstrations of HVS features when we are looking at optical illusions.
- Low-pass filter characteristic (limited number of rods in human eye): see Mach bands
- Lack of colour resolution (fewer cones in human eye than rods)
- Motion sensitivity
- More sensitive in peripheral vision
- Stronger than texture sensitivity, e.g. viewing a camouflaged animal
- Texture stronger than disparity - 3D depth resolution does not need to be so accurate
- Integral Face recognition (babies smile at faces)
- Flicker frequency of film and television using persistence of vision to fool viewer into seeing a continuous image
- Interlaced television painting half images to give the impression of a higher flicker frequency
- Colour television (chrominance at half resolution of luminance corresponding to proportions of rods and cones in eye)
- Image compression (difficult to see higher frequencies more harshly quantised)
- Motion estimation (use luminance and ignore colour)
- Watermarking and Steganography
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