![]() Yes, I'm aware that I could change the alpha channel to black and get a black rather than grey ring around the image. When resizing to a smaller resolution, your border got blended with neighbor pixels, which are white and not black, therefore the grey artifacts. First image is transparent, second is the full sized image with a background, third is resized image with background(I resized it without a background and added it afterwards).įelt like this topic belongs slightly more here than the creative graphics section, and I figure someone here is more likely to know why this is handled the way it is. So could someone explain to me exactly why Bilinear/Bicubic don't treat transparent pixels the exact same way they treat the edge of a rectangular image?Īttached examples of what I'm talking about(may need to zoom in to see all the grayscale artifacts). And the edges do not end up averaged with random grayscale noise. But clearly it can't require eight neighbor pixels to each one - because rectangular images *still* have edges. I understand they're made to average pixels by taking input from surrounding pixels. They fill the transparent pixels up with random grey shades and blend all of the edge pixels in the image with the grayscale noise, which is profoundly stupid as far as I can see. No matter what graphics program you're using. I've noticed that Bilinear/Bicubic resize filters refuse to blend transparent images. set_edgecolor ( 'face' ) for ext in FORMATS : plt. ![]() ![]() ![]() colorbar ( cax = cax, orientation = 'horizontal', ticks = np. plot ( mesh, mesh, marker = '.', ms = 8, color = 'k', lw = 0 ) plt. imshow ( data, interpolation = interp, cmap = COLORS, vmin = 0, vmax = 1 ) plt. meshgrid ( grid, grid ) for interp in METHODS : fig = plt. #!/usr/bin/env python # -*- encoding: utf-8 -*- import sys import numpy as np import matplotlib.pyplot as plt from matplotlib import rcParams rcParams = 18 # Available interpolation methods: # 'none', 'nearest', 'bilinear', 'bicubic', 'spline16', # 'spline36', 'hanning', 'hamming', 'hermite', 'kaiser', 'quadric', # 'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc', 'lanczos' METHODS = FORMATS = COLORS = 'viridis' N = 5 np. ![]()
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