It’s well known that color, brightness and contrast are the primary drivers of digital video quality. These factors are quite often even more important than resolution. Recent color improvements in televisions and video projectors, the desire to enjoy entertainment media on smaller, lower quality devices, and the newer digital color standards have created a unique need for an enhanced video color processing technology using visual perception models to improve the quality of the video experience outside the cinema theater.
To understand visual perception modeling, consider a bed of flowers on a bright sunny day. The flowers look very colorful. As the sun goes down, the flowers appear less colorful and have lower contrast. Did the flowers lose color? No, the physics of flower light absorption and reflection still apply, and the flowers have the same purity of color. What makes them appear less colorful? The answer is the adaption of human vision. As the brightness decreases, the perception of colorfulness and contrast decreases. The human eye adapts. Perceived brightness, colorfulness and contrast are all interrelated. If an image is brighter it looks more colorful. If it is more colorful it looks higher contrast.
A second key element of visual perception modeling is the perception of memory colors such as sky blue and flesh tones. Human vision is highly sensitive to changes in these memory colors, with viewer reaction being quite negative if they don’t look accurate and real. The perception of these memory colors is not only adaptive, but the three dimensional volume of memory colors is difficult to define in any standard color space across all brightness levels. White, brown, red, olive and yellow skin tones at different brightness levels all cover a fairly large three dimensional color volume and can only be well defined mathematically in a perceptually adaptive color space. This makes it more challenging to process flesh tones and other memory colors differently than other colors in an image’s gamut.
An additional factor to consider in driving optimal visual quality is the viewing environment. It is well known that perceptual contrast is reduced if the human eye is adapted to a surround that is brighter or darker than the viewed image. Contrast enhancement has been added to motion picture film viewed in dark cinema theaters since motion film’s inception. This is one reason for the frequent observation, “Movies just look better in theaters than at home.” Including the contrast reduction caused by ambient light adding to the emitted or reflected video image, one can see that contrast enhancement is a prime requirement to fully optimize viewing quality in various viewing environments.
Can a standard display produce a highly accurate rendition of movie images so that a home audience has a professional cinematic experience, despite the effects of their own viewing environment? Is there a way to optimize image perception to effectively take you from any viewing environment into the optimized cinema theater viewing environment? The answer is “Yes.”
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