Here is the code:
import sys, math import numpy as np
import matplotlib.pyplot as plt from skimage import io, color, filters, data from skimage.filters import threshold_otsu import matplotlib.image as mpimg from skimage.restoration import denoise_tv_chambolle, denoise_bilateral import skimage
rawimg = open('1_A.png') img = mpimg.imread(rawimg)
denoised_img = denoise_bilateral(img, sigma_range=0.1, sigma_spatial=15) #denoised_img2 = denoise_tv_chambolle(img, weight=0.1, multichannel=True)
On Thursday, July 30, 2015 at 4:23:34 PM UTC-7, Michael Alonge wrote:
I have an image that I would like to do some smoothing over on.
Lets say there is a faint red spot on a white background. I would like to apply some algorithm that will smooth over the red with the white pixels surrounding the red pixels.
I thought this would be an application for the noise reduction tools ...
... but the picture output looked the same as before.
What is the best algorithm for smoothing over pixels by re assigning a pixel value with the average value of the pixels surrounding it?