Bayer filter

A Bayer filter mosaic is a color filter array (CFA) for arranging RGB color filters on a square grid of photosensors. Its particular arrangement of color filters is used in most single-chip digital image sensors used in digital cameras, and camcorders to create a color image. The filter pattern is half green, one quarter red and one quarter blue, hence is also called BGGR, RGBG, GRBG, or RGGB.

It is named after its inventor, Bryce Bayer of Eastman Kodak. Bayer is also known for his recursively defined matrix used in ordered dithering.

Alternatives to the Bayer filter include both various modifications of colors and arrangement and completely different technologies, such as color co-site sampling, the Foveon X3 sensor, the dichroic mirrors or a transparent diffractive-filter array.

Bryce Bayer's patent (U.S. Patent No. 3,971,065) in 1976 called the green photosensors luminance-sensitive elements and the red and blue ones chrominance-sensitive elements. He used twice as many green elements as red or blue to mimic the physiology of the human eye. The luminance perception of the human retina uses M and L cone cells combined, during daylight vision, which are most sensitive to green light. These elements are referred to as sensor elements, sensels, pixel sensors, or simply pixels; sample values sensed by them, after interpolation, become image pixels. At the time Bayer registered his patent, he also proposed to use a cyan-magenta-yellow combination, that is another set of opposite colors. This arrangement was impractical at the time because the necessary dyes did not exist, but is used in some new digital cameras. The big advantage of the new CMY dyes is that they have an improved light absorption characteristic; that is, their quantum efficiency is higher.

The raw output of Bayer-filter cameras is referred to as a Bayer pattern image. Since each pixel is filtered to record only one of three colors, the data from each pixel cannot fully specify each of the red, green, and blue values 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. These algorithms make use of the surrounding pixels of the corresponding colors to estimate the values for a particular pixel.

Different algorithms requiring various amounts of computing power result in varying-quality final images. This can be done in-camera, producing a JPEG or TIFF image, or outside the camera using the raw data directly from the sensor. Since the processing power of the camera processor is limited, many photographers prefer to do these operations manually on a personal computer. The cheaper the camera, the fewer opportunities to influence these functions. In professional cameras, image correction functions are completely absent, or they can be turned off. Recording in Raw-format provides the ability to manually select demosaicing algorithm and control the transformation parameters, which is used not only in consumer photography but also in solving various technical and photometric problems.

Demosaicing can be performed in different ways. Simple methods interpolate the color value of the pixels of the same color in the neighborhood. For example, once the chip has been exposed to an image, each pixel can be read. A pixel with a green filter provides an exact measurement of the green component. The red and blue components for this pixel are obtained from the neighbors. For a green pixel, two red neighbors can be interpolated to yield the red value, also two blue pixels can be interpolated to yield the blue value.

This simple approach works well in areas with constant color or smooth gradients, but it can cause artifacts such as color bleeding in areas where there are abrupt changes in color or brightness especially noticeable along sharp edges in the image. Because of this, other demosaicing methods attempt to identify high-contrast edges and only interpolate along these edges, but not across them.