![]() Instead, in terms of digital image processing, brightness is more properly described as the measured intensity of all the pixels comprising an ensemble that constitutes the digital image after it has been captured, digitized, and displayed. After the necessary brightness and contrast adjustments have been made to a digital image, the user can select another settings panel to apply the changes or click on the Panel Reset button to return the image to its original settings.īrightness should not be confused with intensity (more accurately termed radiant intensity), which refers to the magnitude or quantity of light energy actually reflected from or transmitted through the specimen by the microscope illuminator. In a manner similar to that in the tutorial, moving the MIC-D software sliders to the left (towards the minus (-) icon) decreases brightness and contrast of the image displayed in the interface window, while moving the sliders to the right (closer to the plus (+) icon) increases values of these parameters. After an image has been captured with the microscope's CMOS image sensor, it can be imported into the image processing software and adjusted with respect to brightness and contrast by varying the appropriate slider positions in the Image Settings Panel (see Figure 1). In contrast, translating the brightness slider to the right increases image brightness and shifts the histogram levels to higher input pixel brightness values.īrightness and contrast adjustments that are analogous to those described in the tutorial are available in the Olympus MIC-D digital microscope image processing software, as illustrated in Figure 1. Moving the brightness slider to the left of center position decreases image brightness and shifts the histogram to lower input pixel brightness values. The specimen brightness level can be adjusted with the Brightness Level slider or its accompanying blue arrow buttons, in a manner analogous to that described above for the contrast controls. Visitors should note that the height of the histogram graph is scaled according to the number of pixels displayed at the top left of the vertical axis (labeled Pixel Count). The digital microscope image, histogram, and intensity transfer function graphs are continuously updated as the contrast level is varied with the slider. The slider can be translated either by dragging with the mouse cursor, or by clicking on the blue arrow buttons. ![]() Moving the slider to the left of the center position decreases image contrast, while moving the slider to the right increases image contrast. To operate the tutorial, select an image from the Choose A Specimen pull-down menu, and vary the contrast level with the Contrast Level slider (or arrow buttons). The contrast level of the specimen image is adjustable with the Contrast Level slider and/or a set of blue arrow buttons. ![]() Radio buttons are utilized to toggle between these contrast modes. Two contrast adjustment mode controls are available in the tutorial, which correspond to specific contrast adjustment algorithms for Grayscale Contrast and RGB Contrast. Selecting the Red, Green, or Blue checkboxes will display the histogram for the corresponding color channel of the image in the RGB Histogram window (the default position is all three boxes checked). Visitors will note that specimens captured using the various techniques available with the MIC-D microscope behave differently during image processing in the tutorial.Īdjacent to the Specimen Image window is a graph that displays the RGB/Grayscale Histogram of the microscope image (black or colored vertical bars), along with the intensity transfer function (black curve). The following nomenclature is used: ( BF), brightfield ( DF), darkfield ( OB), oblique illumination and ( RL), reflected light. Each specimen name includes, in parentheses, an abbreviation designating the contrast mechanism employed in obtaining the image. The tutorial initializes with a randomly selected specimen image, captured in the MIC-D digital microscope, appearing in the left-hand window entitled Specimen Image. This interactive tutorial explores the wide range of adjustment that is possible in digital image brightness and contrast manipulation, and how these variations affect the final appearance of the image. We are sorry, but this Java tutorial is no longer available.
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