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Digital Visual Media Forensics
Published in S. Ramakrishnan, Cryptographic and Information Security, 2018
Acquisition of the digital visual data begins with light passing through the camera lens and possibly through a filter (which is generally used to remove infrared or ultra-violet light). Color cameras contain an additional Color Filter Array (CFA), which is placed over the sensor to generate different color channels. An RGB Bayer Pattern, also known as a Bayer filter mosaic, is the most commonly used CFA. It is a 2 × 2 array that contains alternative rows of red and green, and green and blue filters (Figure 23.11a). A demosaicing (aka debayering or demosaicking) algorithm then reconstructs a full color image using the incomplete color samples output from a CFA-overlaid sensor; this process is known as CFA interpolation or color reconstruction. An alternative CFA configuration is the CMYK subtractive color model; it is relatively lesser known and is only available in very few high-end sensors.
Color Image Interpolation
Published in Fathi E. Abd El-Samie, Mohiy M. Hadhoud, Said E. El-Khamy, Image Super-Resolution and Applications, 2012
Fathi E. Abd El-Samie, Mohiy M. Hadhoud, Said E. El-Khamy
Color image interpolation or demosaicking is a process by which a raw image generated by a digital still camera with the help of a color filter array (CFA) is converted to a full color image by estimating the missing color components of each pixel from its neighbors. In order to reduce the cost of digital still cameras used to capture color images, each camera uses a single charge-coupled device (CCD) instead of three CCDs [43,44]. The CFA consists of a set of spectrally selective filters arranged in a certain interleaved pattern so that each sensor pixel samples only one of the three primary color components. In digital still cameras, color images are encoded by the CFA pattern, and a subsequent interpolation process produces full color images.
Imaging Systems
Published in Takao Kuroda, Essential Principles of Image Sensors, 2017
As only one filter color is formed at each pixel in a one-sensor color camera system, only one piece of color information is obtained at each pixel. On the other hand, the human eye and brain perceive a color by a set of R, G, and B, as mentioned in Section 6.4. Therefore, all R, G, and B information is necessary at each pixel to construct a color image for applications for humans to watch. Demosaicking creates color signals that are not captured originally at each pixel.
Colour filter array demosaicking: a brief survey
Published in The Imaging Science Journal, 2018
M. S. Safna Asiq, W. R. Sam Emmanuel
False colour artefacts are the distortion caused by the perverted shifts across the boundaries. The signals in the image faces, peaks and troughs of a different colour filter in adjacent pixels during the high-frequency monochrome pattern observation. These images are interpreted to have different colours in it causing false colour artefact. This can be overcome by taking into account the spectral correlation between the pixel values. The examples of the artefacts are illustrated in Figure 6. Almost all demosaicking algorithms confront the problem of artefacts in the demosaicked image. Special attention is given to artefacts in (22)–(27).
Colour filter array demosaicking over compression through modified grey wolf optimization technique
Published in The Imaging Science Journal, 2018
M. S. Safna Asiq, W. R. Sam Emmanuel
Demosaicking is the process of estimating the missing intensity value of the raw image to a complete or a full colour image. The compressed image is demosaicked by a four directional demosaicking across the edges and not along the edges [5]. The image is reconstructed by utilizing the compressed image obtained after the above process. The image is converted to a mosaic in order to demosaic the compressed image to obtain a better reconstructed image with effective results. The demosaicking process is divided into green intensity value demosaicking and red/blue intensity value demosaicking.