In Astronomy, sometimes the images send by satellite/telescope could be Blur and one would be interested to make the image Sharpe. The Kernel (it is matrix representation) is to process the image -from Blur image to Sharpe Image. Convolution Matrix, Mask, Matrix/Array are the other names given to the Kernel. Below is the example of Mars Surface Blur Image Image Credit: NASA/JPL-Caltech Below is the processed image which has now become Sharpe Image Please open both images to see the effect.7 Below is the python code used. ****************************************************************** # load the required packages import cv2 import numpy as np # load the image into system memory image = cv2.imread('E:\\astronomy_related\\blurr_to_clear_image\\marssurface_blurr.jpg', flags=cv2.IMREAD_COLOR) # display the blurr image to the screen cv2.imshow('Mars Surface blurr...
In Astronomy, Image taken by cameras would be based on specific filters(channels)-Red, Green, Blue. Below are the the images taken across 3 channels. Red(Left), Green(Centre), Blue(Right) Original image credit(single image which is not shown here)- Credits: NASA, ESA, J. Hester and A. Loll (Arizona State University) Below is result after combining above 3 channel images Below is the python code used. Original Carb Nebula image is spitted into 3 channels(as shown 3 gray images above) *************************************************** from PIL import Image # Open the red, green, and blue channel images red_channel = Image.open('E:\\astronomy_related\\rbg_one\\red.png') green_channel=Image.open('E:\\astronomy_related\\rbg_one\\green.png') blue_channel =Image.open('E:\\astronomy_related\\rbg_one\\blue.png') # Create a new RGB image result = Image.merge("RGB", (red_channel, green_channel, blue_channel)) # Save the result image result.save('E:\\astr...
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