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Digital Image Processing Systems
Published in Scott E. Umbaugh, Digital Image Processing and Analysis, 2017
Grayscale images are referred to as monochrome (“one color”) images. They contain brightness information only, no color information. The number of bits used for each pixel determines the number of different brightness levels available. The typical image contains 8 bits per pixel data, which allows for 256 different brightness (gray) levels, values of 0–255. This representation provides more than adequate brightness resolution, in terms of the human visual system's requirements (see Chapter 7), and provides a “noise margin” by allowing for approximately twice as many gray levels as required. This noise margin is useful in real-world applications due to many different types of noise, or false information in the signal, that is inherent in real systems. Additionally, the 8-bit representation is typical due to the fact that the byte, which corresponds to 8-bits of data, is the standard small unit in the world of digital computers. Figure 2.4-2 shows typical monochrome, grayscale, or gray-level, images.
Image processing
Published in Geoff Lewis, Communications Technology Handbook, 2013
At the basic level, images can be displayed in monochrome (black and white) by simply using the brightness variation of each scanning line (the luminance signal). The addition of colour to the images considerably increases the amount of information that has to be processed. This includes hue which identifies the colour and saturation which describes the degree to which the colour is diluted with white light. Most of the colours that appear in nature can be created by the addition in suitable proportions of red, green and blue light, these being referred to as primary colours. White light can be formed by summing suitable levels of red (R), green (G) and blue (B) light. Thus the luminance signal (Y) can be formed from, Y = R + G + B, to provide a monochrome signal. An alternative system uses a luminance and two colour difference signals Y, R–Y, B–Y, concept. Because the green component is contained in Y, G can be recovered by suitable processing. In either case, three signal components have to be processed.
Real-Time Alarm Clock Using Arduino
Published in Anudeep Juluru, Shriram K. Vasudevan, T. S. Murugesh, fied!, 2023
Anudeep Juluru, Shriram K. Vasudevan, T. S. Murugesh
is used for initializing the I2C communication between the OLED module and Arduino Uno. is used for clearing any data on the OLED screen. is used to set the font size of the text displayed on the OLED screen. is used to set the text colour displayed on the OLED screen. For a monochrome display, you can choose between white and black text colours. considered as white colour, whereas is considered as black colour. display.begin(SSD1306_SWITCHCAPVCC, OLED_ADDRESS); //Initialize OLED module //Initial display configuration display.clearDisplay(); display.setTextSize(1); display.setTextColor(SSD1306_WHITE);
Anterior Segment Optical Coherence Tomography in Pediatric Ocular Pathology: Imaging Study of 115 eyes
Published in Expert Review of Medical Devices, 2023
Images were obtained at the horizontal (0° and 180°), vertical (90° and 270°) and oblique meridians (135° and 315°; 45° and 225°) as well. The examination was carried out in the sitting position for young children with the standard chin and forehead mounted-device. The height of the chin rest was adjusted for each patient. For smaller children, this was done in the standing position. Even smaller children were held in their laps by their parents. It is a non-contact device, with no need for any anesthesia. The AS-OCT images obtained by our device are in grayscale or monochrome, representing the backscattered light intensity in a cross-sectional scheme. The grayscale is directly related to the tissue reflectivity. False colors may be used to delineate the boundaries of various structures like the corneal layers but may create artificial boundaries.
An Optimum Shift-and-Weighted brightness mapping for low-illumination image restoration
Published in The Imaging Science Journal, 2019
Yeping Peng, Haiyan Shi, Hongkun Wu, Ruowei Li, Ngaiming Kwok, San Chi Liu, Shilong Liu, Md Arifur Rahnam
Other than the separation-based approach, the low-illumination problem was tackled using appropriate input-output intensity mappings. In [16], the Nonlinear Transfer Function based Local Approach (NTFLA) method was reported. A monochrome image is first extracted from the colour channels. For example, in the Hue-Saturation-Intensity (HSI) colour space the intensity is the average of colour channels, and in the Hue-Saturation-Value (HSV) space the intensity is the maximum of the colours. The input intensity is then mapped to the output intensity bywhere is the parameters obtained from a set of thresholds on . The final enhanced image is resulted from passing in a series of nonlinear processes which operate on each colour channel.
Image Analytics: A consolidation of visual feature extraction methods
Published in Journal of Management Analytics, 2021
Xiaohui Liu, Fei Liu, Yijing Li, Huizhang Shen, Eric T.K. Lim, Chee-Wee Tan
A digital image is a multidimensional matrix of pixel values. We denote an image as such that represents the size of the focal image (i.e. the number of pixels). Depending on its resolution, an image is encoded as a matrix in computer graphics where and indicate the number of rows and columns of the focal image’s pixel grid, respectively. The intensity of each pixel at the location can be represented in distinct color spaces including but not limited to RGB (Red, Green, Blue), Grayscale, YUV, HSV (Hue, Saturation, Value/Brightness), and HSL (Hue, Saturation, Luminance or lightness) (Reinhard et al., 2001). RGB is a fundamental color space in which the value of each pixel encodes red (R), green (G) and blue (B) components of the color of the pixel (Reinhard et al., 2001). The RGB values of pixels can be directly converted into grayscale by employing colorimetry and photometry techniques. The transformed monochrome image possesses the same luminance as the original color image. YUV is a variation of RGB color space that compresses the R, G, B components of pixels in a more human-friendly manner (Ibraheem et al., 2012; Sural et al., 2002). Y measures the brightness of the color (i.e. the luminance) and U/V portrays the color itself (i.e. the chrominance). HSV and HSL, alternative representations of RGB, are cylindrical color spaces that take human vision into account in color encoding (Ibraheem et al., 2012; Sural et al., 2002) (see Figure 1).