Image processing engine

The image processing engine, or image processor, is an important component of a digital camera and plays a vital role in creating the digital image.

The image processing engine must perform a complex range of tasks.

The photodiodes employed in an image sensor are colour-blind by nature: they can only record shades of grey. To get colour into the picture, they are covered with different colour filters: red, green and blue (RGB) according to the pattern designated by the Bayer filter - named after its inventor. As each photodiode records the colour information for exactly one pixel of the image, without an image processor there would be a green pixel next to each red and blue pixel. (Actually, with most sensors there are two green for each blue and red diodes.)

The image processing engine comprises a combination of hardware processors and software algorithms. The image processor gathers the luminance and chrominance information from the individual pixels and uses it to compute/interpolate the correct colour and brightness values for each pixel. If it does this well, the result is an image with natural and pleasing colours, balanced contrast and appropriate sharpness.

This process, however, is quite complex and involves a number of different operations. Its success depends largely on the "intelligence" of the algorithms applied.

Demosaicing

As stated above, the image processor evaluates the colour and brightness data of a given pixel, compares them with the data from neighbouring pixels and then uses a demosaicing algorithm to produce and appropriate colour and brightness value for the pixel. The image processor also assesses the whole picture to guess at the correct distribution of contrast. By adjusting the gamma value (heightening or lowering the contrast range of an image's mid-tones) subtle tonal gradations, such as in human skin or the blue of the sky, become much more realistic.

Noise reduction

Noise is a phenomenon found in any electronic circuitry. In digital photography its effect is often visible as random spots of obviously wrong colour in an otherwise smoothly-coloured area. Noise increases with temperature and exposure times. When higher settings are chosen the electronic signal in the image sensor is amplified, which at the same time increases the noise level, leading to a lower signal-to-noise ratio. The image processor attempts to separate the noise from the image information and to remove it. This can be quite a challenge, as the image may contain areas with fine textures which, if treated as noise, may lose some of their definition.

Image sharpening

As the colour and brightness values for each pixel are interpolated some image softening is applied to even out any fuzziness that has occurred. To preserve the impression of depth, clarity and fine details, the image processor must sharpen edges and contours. It therefore must detect edges correctly and reproduce them smoothly and without over-sharpening.

Speed

With the ever higher pixel count in image sensors, the image processor's speed becomes more critical: photographers don't want to wait for the camera's image processor to complete its job before they can carry on shooting - they don't even want to notice some processing is going on inside the camera. Therefore, image processors must be optimised to cope with more data in the same or even a shorter period of time.

Individual manufacturers have named their image processing engines differently: Canon's is called DiG!C, Olympus' TruePic, and Panasonic's the VENUS Engine.

See also

*Image processing
*Digital image processing
*Digital image editing
*Demosaicing