A demosaicing (also de-mosaicing, demosaicking or debayering) algorithm is a used to reconstruct a full color image from the incomplete color samples output from an overlaid with a color filter array (CFA). It is also known as CFA interpolation or color reconstruction.
Most modern digital cameras acquire images using a single image sensor overlaid with a CFA, so demosaicing is part of the required to render these images into a viewable format.
Many modern digital cameras can save images in a allowing the user to demosaic them using software, rather than using the camera's built-in firmware.
The aim of a demosaicing algorithm is to reconstruct a full color image (i.e. a full set of color triples) from the spatially undersampled output from the CFA. The algorithm should have the following traits:
Avoidance of the introduction of false color artifacts, such as chromatic aliases, zippering (abrupt unnatural changes of intensity over a number of neighboring pixels) and purple fringing
Maximum preservation of the
Low computational complexity for fast processing or efficient in-camera hardware implementation
Amenability to analysis for accurate noise reduction
Color filter array
A color filter array is a mosaic of color filters in front of the image sensor. Commercially, the most commonly used CFA configuration is the Bayer filter illustrated here. This has alternating red (R) and green (G) filters for odd rows and alternating green (G) and blue (B) filters for even rows. There are twice as many green filters as red or blue ones, catering to the human eye's higher sensitivity to green light.
Since the color subsampling of a CFA by its nature results in aliasing, an optical anti-aliasing filter is typically placed in the optical path between the image sensor and the lens to reduce the false color artifacts (chromatic aliases) introduced by interpolation.
Since each pixel of the sensor is behind a color filter, the output is an array of pixel values, each indicating a raw intensity of one of the three filter colors.
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
An image sensor or imager is a sensor that detects and conveys information used to form an . It does so by converting the variable attenuation of light waves (as they pass through or reflect off objects) into signals, small bursts of current that convey the information. The waves can be light or other electromagnetic radiation. Image sensors are used in electronic imaging devices of both analog and digital types, which include digital cameras, camera modules, camera phones, optical mouse devices, medical imaging equipment, night vision equipment such as thermal imaging devices, radar, sonar, and others.
In digital imaging, a color filter array (CFA), or color filter mosaic (CFM), is a mosaic of tiny color filters placed over the pixel sensors of an to capture color information. The term is also used in reference to e paper devices where it means a mosaic of tiny color filters placed over the grey scale display panel to reproduce color images. Color filters are needed because the typical photosensors detect light intensity with little or no wavelength specificity and therefore cannot separate color information.
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 s used in digital cameras, camcorders, and scanners 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.
Image super-resolution reconstructs a higher-resolution image from the observed low-resolution image. In recent years, machine learning models have been widely employed and deep learning networks have achieved state-of-the-art super-resolution performance. ...
Direct visualization is often sought to elucidate flow patterns and validate models to predict the filling kinetics during processes whereby a liquid resin infiltrates a textile porous preform. Here, X-ray phase contrast interferometry is evaluated to imag ...
Fluorescence lifetime imaging microscopy (FLIM) is an imaging modality often used to monitor biochemical properties of a cell or a tissue. In addition to conventional fluorescence microscopy features, such as selective labeling and non-invasiveness, FLIM e ...