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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.
Color image processing for digital cameras
Published in Sharma Gaurav, Digital Color Imaging Handbook, 2017
To provide a color image, each cell of the sensor array is covered with a transmissive filter of a particular color to form a color filter array (CFA). Although many different CFA patterns have been developed, the most popular patterns are the two shown in Figure 12.6. The RGB Bayer pattern has 50% green cells arranged in a checkerboard and alternating lines of red and blue cells. The complementary mosaic pattern24 has equal proportions of magenta (M)-, green (G)-, yellow (Y)-, and cyan (C)-sensitive photosites arranged in magenta–green and yellow–cyan rows. The position of the green–magenta columns is staggered by one pixel on alternate green–magenta rows.
A fresh look at computer vision for industrial quality control
Published in Quality Engineering, 2022
Bart De Ketelaere, Niels Wouters, Ioannis Kalfas, Remi Van Belleghem, Wouter Saeys
A CV system generally consists of four components, being illumination, camera system, computer hardware and software. In its classical form, a vision system tries to mimic human vision in terms of color sensitivity. To achieve this a light source is used to mimic natural light. Nowadays, most often this light source is a white LED lamp because it provides a rather flat intensity all over the visible part of the electromagnetic spectrum (400 to 700 nm). A camera is then used to capture the scene of interest. Most cameras used in industry are silicon-based Complementary Metal-Oxide Semiconductors (CMOS), and can be panchromatic or color cameras. The panchromatic cameras integrate all light in their photosensitive region (400 nm to 1000 nm), which is broader than the visible region alone. Color cameras, in contrast, typically use a color filter array for arranging Red, Green and Blue (hence the name RGB) color filters on their digital image sensors. The digital image is then fed to a computer where it can be stored and (pre-)processed. The preprocessing stage mainly handles issues such as noise, non-uniform illumination, geometric distortion, improper focus, amongst others, and highlights regions and features that can be used for the actual processing task (Brosnan and Sun 2004).
Lensless broadband diffractive imaging with improved depth of focus: wavefront modulation by multilevel phase masks
Published in Journal of Modern Optics, 2019
Vladimir Katkovnik, Mykola Ponomarenko, Karen Egiazarian
To produce a multiwavelength full colour image we need at least three colour (RGB) components at each pixel location. This can be achieved by three exposures, each of which registers a light of the specific colour, for instance, by a single broadband sensor with the three RGB filters. To reduce the complexity and the cost, most digital cameras use a single sensor covered by CFA. To render a full colour image from these CFA samples an image processing called demosaicing is used.
Demosaicing Method for Multispectral Images Using Derivative Operations
Published in American Journal of Mathematical and Management Sciences, 2021
Commonly used RGB color cameras can be treated as single-camera-single-shot systems. These RGB cameras consist of single imaging sensor along with color filter array (CFA) in front of the sensor. Most commonly used CFA is Bayer CFA (Bayer, 1976), as shown in Figure 1(a). Using CFA in RGB cameras, only one color sample is acquired at each pixel location, and this acquired image data is called CFA image or mosaiced image. Other missing color samples are estimated through neighboring pixels in CFA image. To reconstruct the full RGB color image by evaluating missing color samples from raw CFA image (mosaiced image), reconstruction operation, called CFA demosaicing, is applied. There are many CFA demosaicing methods which have been proposed for RGB imaging system (Goyal et al., 2014; Lossona et al., 2010; Popescu & Farid, 2005). The idea of an extension of single-camera-one-shot systems for multispectral imaging using multispectral filter array (MSFA) in multispectral domain provides the advantage of low cost, less weight and real time video capture. An MSFA is a mosaic pattern similar to CFA with each element being a wavelength specific optical filter. Multispectral camera along with multispectral filter array (MSFA) captures only one spectral band information at each pixel location, and the captured image is called MSFA image. To reconstruct the full multispectral image from an MSFA image, the reconstruction operation, called MSFA demosaicing or multispectral image demosaicing, is required. However, extension from CFA to MSFA and CFA demosaicing to MSFA demosaicing is not directly generalized because of very sparse sampling of each spectral band in MSFA. The Bayer CFA pattern is designed based on a human visual system. As the human eye is more sensitive to green color, 50% samples are of green color, 25% samples are of red color and remaining 25% samples are of blue color in Bayer CFA, as shown in Figure 1(a). But designing an MSFA pattern is a challenging task because of a large number of bands and each with specific characteristics. Some of the MSFA patterns are shown in Figure 1(b–e). Brauers and Aach (2006) proposed six-band MSFA pattern 2 × 3 grid, as shown in Figure 1(b). Aggarwal and Majumdar (2014, 2015) presented two different types of MSFA patterns: random MSFA pattern and uniform multispectral filter array (UMSF, as shown in Figure 1(c) for N bands). Figure 1(d) shows a 5-band MSFA used by Monno et al. (2012) and Monno et al. (2015), and a simple 16-band MSFA, as used by Mihoubi et al. (2015), is shown in Figure 1(e).