Color is a psychological phenomenon based on the interaction of the spectrum of light (distribution of light energy versus wavelength) with light receptors in the eye, which have specific sensitivities for specific spectral wavelength bands or regions (hereinafter “spectral components”) of light. Color categories and physical specifications of color are also associated with objects, materials, light sources, etc., based on their physical properties such as light absorption, reflection, or emission spectra.
In the physical sense, a color is the ratio of intensities measured in different spectral components of the electromagnetic spectrum. In the physiological sense, in humans, the different spectral components are defined by the spectral sensitivity curves of three different types of receptors in the eye (i.e., the so-called red, blue, and green cones). The human brain processes and combines signals from the red, blue and green cones to create a composite impression or image of a scene. All colors in the scene are perceived as combinations of the red, blue and green cone signals. The range or gamut of colors that are perceived by humans is represented, for example, by the CIE 1931 chromaticity diagram.
Man-made color image sensors (e.g., color film, or digital cameras using CCD or CMOS sensors) also sense light intensities in a finite number of distinct spectral components. Various types of color image sensors differ in how they separate and measure the distinct spectral components. For example, a color film may have a stack of three different emulsion layers that are exposed by red, green, and blue components of light, respectively. A digital camera may use an array of layered sensors so that every pixel, like a color film, contains a stack of sensors sensitive to individual colors (e.g., sensors available under the Foveon trademark). More commonly, digital cameras or other man-made color image sensor arrangements use a spatial color filter array (e.g., a Bayer color filter array) positioned on top of a CMOS or CCD sensor to capture different spectral components of light in corresponding nominal pixel types.
The man-made color image sensor arrangements sense and collect intensity data for each distinct spectral component received from a scene. The data for each spectral component is monochrome, i.e., it includes only intensity information, but no color information. To create an approximate color image or rendition of a scene, the different intensity data for the distinct spectral components are processed, encoded to certain colors and intensities, and combined.
A three-color Bayer color filter array is used in most single-chip digital image sensors (in digital cameras, camcorders, and scanners) to create a color image. A Bayer filter mosaic is a color filter array for arranging red (R), green (G), blue (B) color filters on a square grid of photosensors. The filter pattern is typically 50% green, 25% red and 25% blue. FIG. 1, which is adapted from Bayer U.S. Pat. No. 3,971,065, shows another exemplary Bayer filter mosaic pattern with red, blue and green color transmissive filters arranged in a repeating pattern. In this pattern, luminance elements (green, denoted by a “G”) assume every other array position. Chromacity elements (red, denoted by an “R”) alternate with the G luminance elements in alternate rows. The R elements also alternate with other chromacity elements (blue, denoted by a “B”) in filling the remaining array positions.
The Bayer filter mosaic patterns are designed to mimic the human eye's greater resolving power with green light. For example, in the Bayer color filter array shown in FIG. 1, B elements contribute only one-eighth of the element population in recognition of the human visual system's relatively limited ability to discern blue detail. Red detail, to which the human visual system is more responsive, is sampled at a higher rate than for blue detail by virtue of the relatively greater population of the R elements. Luminance detail, to which the human eye is most responsive, is sampled at the highest rate by the large population of G elements in the array.
The raw output of a Bayer-filter image sensor may be referred to as a Bayer pattern image. Since each pixel of the image sensor is filtered to record only one of three colors, the data from each pixel does not fully determine color on its own. To obtain a full-color image, various demosaicing algorithms can be used to interpolate a set of complete red, green, and blue values for each pixel of the image sensor.
Other types of three- and four-color filter arrays suggested for use with man-made color image sensors are also based on luminance-chrominance considerations to mimic the human eye's perception of color. (See e.g., Roddy et al. U.S. Pat. No. 7,057,654, Bawolek et al. U.S. Pat. Nos. 6,771,314 B1 and 5,914,748, Vook et al. U.S. Pat. No. 6,771,314B1, Silverstein et al. U.S. Pat. No. 4,800,375, Merril et. al. U.S. Pat. No. 5,965,875, and Chang U.S. Patent Application Publication No. US2007/0145273 A1).
In any imaging system, diffraction sets a fundamental image resolution limit that depends only on the aperture's f-stop (or f-number) setting of the image sensor optics, and on the wavelength of light being imaged. The foregoing color filter arrays, which are based on luminance-chrominance considerations, do not address the wavelength-dependent diffraction effects that can occur with the image sensor optics.
Consideration is now being given to color filter arrays for color imaging when diffraction effects caused by image sensor optics may be significant.