Short communicationA simple parametric equation for pseudocoloring grey scale images keeping their original brightness progression
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Effective hybrid attention network based on pseudo-color enhancement in ultrasound image segmentation
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2022, Journal of Experimental Marine Biology and EcologyCitation Excerpt :Yet, the human eye has limited ability to distinguish between different levels of gray (Yu et al., 2018). Pseudo (false)-coloring can be performed to enhance contrast (Lehmann et al., 1997). The so-called look-up tables (LUTs) are used to convert a grayscale image to a colored image by replacing the values of pixels with colors (Arnavut et al., 1998).
Automatic color segmentation of breast infrared images using a Gaussian mixture model
2015, OptikCitation Excerpt :Although a gray level image has advantages of simplicity and a natural sense of order, the main disadvantages are its limited number of just noticeable differences (60 to 90 JNDs) and poor contrast between adjacent gray levels [19]. Since human visual system is more sensitive to color images than gray ones, transforming gray level images to pseudo-color images visually enhances the image and makes the details of the image to be more explicit; therefore targets could be recognized more easily [20]. In [21] a frequency domain pseudo color algorithm was proposed to enhance ultrasound images.
Pseudocolours for thermography - Multi-segments colour scale
2015, Infrared Physics and TechnologyCitation Excerpt :The colour scale not only possesses perceptual linearity, it also maximizes just-noticeable-differences among hues in an orderly fashion [4]. Whereas Lehmann et al. [8] formulated a simple parametric equation to map grey scale to colour scale. The equation, controlled by frequency and phase, can produce various colour scales that are almost perceptually linear and vary across hues, as illustrated in Fig. 2.
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