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Bayer filter

Color filter array

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Through Human eye, Pixel and Algorithm

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.

Explanation

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. Although digital CMY sensors have appeared in some older digital cameras, all modern consumer digital cameras use RGB sensitive sensors. The advantage of CMY dyes is that they have an improved light absorption characteristic, but this has been at the cost of lower fidelity conversion to the necessary RGB wavelengths necessary in light emitting displays.

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.

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