Change channel image mixer1/6/2023 Generally speaking, for a well-exposed original, the total value of the sliders' fields should be about 100. Now play with the sliders, keeping in mind your evaluation of the individual channels. Start with the three channel sliders at +40 and the Constant slider at about -7. Adjust the sliders to create a great grayscale image. (Although this discussion is about creating a tremendous grayscale image, that resulting channel could be used in a variety of ways in other images, perhaps as an alpha channel or a spot color channel.)Ĥ. When you select the Monochrome option (lower-left corner of the dialog box), you're telling the Channel Mixer that you want one single channel when you're finished with the adjustment. (The Channel Mixer is also available as an adjustment layer.) Use the menu command ImageOAdjustmentsOChannel Mixer. Make sure to click the RGB channel when you're done evaluating, or the Channel Mixer won't be available. Foliage, for example, will usually be most prominent in the Green channel. See which channel holds detail information for which part of your image. Take a look at each channel individually by clicking it and hiding the other two color channels by clicking the eyeball icon to the left of each. Open the image in Photoshop and evaluate the color channels. But none of those techniques quite compares to creating grayscale with the Channel Mixer. You can create grayscale versions of your images in a variety of ways in Photoshop - by choosing ImageOAdjustmentsODesaturate or ImageOModeOGrayscale, for example, or by deleting channels, using the L channel of a Lab image, and so forth. There is one thing that Channel Mixer does incredibly well, and it's even practical, too. You can produce some incredible (and incredibly weird) effects with this technique, partially inverting one or two channels. If you drag a slider to the left past 0 (zero), you invert the content of the channel. Generally speaking, you want to add an amount (combined between the two other channels) just about equal to what you subtract from the target channel. You then drag one or both of the other sliders toward the right. You reduce the value of the target channel by dragging the slider to the left. Should you come across an image with damage in one channel, you can certainly use the Channel Mixer adjustment to work on it (with some degree of success). The calculated channel values produced by the 3 functions can differ from one another by 1, due to the differences in the way they perform the calculations, but of course such differences aren't readily visible.Designed to repair a defective channel in an image, Channel Mixer lets you use sliders to replace some or all of the intensity of one color channel with content from the others. Out_data = np.stack((r.T, g.T, b.T), axis=2).astype('uint8')įWIW, that output image was created using comp_mean_npB. In_data = np.asarray(img, dtype='uint16') # if we want to do more sophisticated operations # Do the arithmetic using 'uint16' arrays, so we don't need # Do the arithmetic using 'uint8' arrays, so we must be Or by converting the pixel data to a Numpy array and This can be done using PIL's own ImageChops functions Replace each RGB channel by the mean of the other 2 channels, i.e., Here's a script that shows two different Numpy approaches, as well as an approach based on kennytm's ImageChops code. fromarray method to load image data from a Numpy array. Numpy provides a function np.asarray which can create a Numpy array from PIL data. And you can do all sorts of mathematical operations in Numpy, or using related libraries, like SciPy. #Change channel image mixer code#So the speed of Numpy code is comparable to the speed of using ImageChops. Numpy uses native machine data types and its compiled routines can processes array data very quickly compared to doing Python loops on Python numeric objects. An alternative to using PIL.ImageChops is to convert the image data to a Numpy array.
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