[PYTHON] [Image processing] Posterization

1. Overview

Introducing "Posterization", the basic technology of image processing. Posterization is a conversion using a tone curve on the stairs, which limits the output pixel value to several levels.

As shown in the figure below, the pixel value of the input image is set to n levels (4 levels in the figure below) to limit the pixel value of the output image. By doing so, the borders become clearer and you can express colors like art.

Posterization is a book ["Digital Image Processing"](https://www.amazon.co.jp/%E3%83%87%E3%82%A3%E3%82%B8%E3%82%BF%E3% 83% AB% E7% 94% BB% E5% 83% 8F% E5% 87% A6% E7% 90% 86-% E6% 94% B9% E8% A8% 82% E7% AC% AC% E4% BA % 8C% E7% 89% 88-% E3% 83% 87% E3% 82% A3% E3% 82% B8% E3% 82% BF% E3% 83% AB% E7% 94% BB% E5% 83% 8F% E5% 87% A6% E7% 90% 86% E7% B7% A8% E9% 9B% 86% E5% A7% 94% E5% 93% A1% E4% BC% 9A / dp / 490347464X / ref = asc_df_490347464X /? tag = jpgo-22 & linkCode = df0 & hvadid = 342595526565 & hvpos = & hvnetw = g & hvrand = 5492134153117811443 & hvpone = & hvptwo = & hvqmt = & hvdev = c & hvdvcmdl = & hvlocint = & hvlocphy = 1937 It follows the processing method that is used. Since the tone curve that leaves pixel values 0 and 255 in the processed image is used, the image has a clear contrast.

2. Environment

The environment in which the posterization process was tried is as follows.

Python 3.6.8 numpy 1.18.1 matplotlib 3.1.2 opencv-python 4.1.2.30

Since OpenCV is used in the library, please install it in advance.

pip install opencv-python

3. Code

When I looked at various sites about posterization, many sites used LUTs that did not reflect white with a pixel value of 255 in the output image.

This process also reflects the pixel value of 255 "white" in the output image, so I devised a LUT creation. The input and output of bins are separated, but please refer to the comment section of the code for details.

posterization.py

#coding: utf-8
import cv2
import numpy as np
import matplotlib.pyplot as plt

def main():
    img = cv2.imread('image.jpg')                   #Loading images
    gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)    #Grayscale
    n = 4                                           #Number of pixel value divisions

    pos = posterization(gray, n)
    cv2.imwrite('pos.jpg', pos)          #Output of posterized image

def posterization(img, n):
    x = np.arange(256)                   #0,1,2...An array of integers up to 255

    ibins = np.linspace(0, 255, n+1)     #Input from LUT is 255/(n+1)Split with
    obins = np.linspace(0,255, n)        #Output from LUT is 255/Split by n

    num=np.digitize(x, ibins)-1          #Number the input pixel values to posterize
    num[255] = n-1                       #Correct the number of pixel value 255 that is off by digitize processing

    y = np.array(obins[num], dtype=int)   #Create a posterizing LUT
    pos_LUT(n, y)                         #Create LUT diagram
    pos = cv2.LUT(img, y)                 #Perform posterization

    return pos

#Posterization LUT diagram creation
def pos_LUT(n, y):
    x = np.arange(0,256,1)
    plt.plot(x,y)
    plt.savefig("pos_LUT.png ")

if __name__=='__main__':
    main()

4. References

★ Books ・ [Digital Image Processing [Revised Second Edition](Public Interest Incorporated Foundation Image Information Education Promotion Association (CG-ARTS))] [0] [0]:https://www.amazon.co.jp/%E3%83%87%E3%82%A3%E3%82%B8%E3%82%BF%E3%83%AB%E7%94%BB%E5%83%8F%E5%87%A6%E7%90%86-%E6%94%B9%E8%A8%82%E7%AC%AC%E4%BA%8C%E7%89%88-%E3%83%87%E3%82%A3%E3%82%B8%E3%82%BF%E3%83%AB%E7%94%BB%E5%83%8F%E5%87%A6%E7%90%86%E7%B7%A8%E9%9B%86%E5%A7%94%E5%93%A1%E4%BC%9A/dp/490347464X/ref=asc_df_490347464X/?tag=jpgo-22&linkCode=df0&hvadid=342595526565&hvpos=&hvnetw=g&hvrand=5492134153117811443&hvpone=&hvptwo=&hvqmt=&hvdev=c&hvdvcmdl=&hvlocint=&hvlocphy=1009247&hvtargid=pla-889374643658&psc=1&th=1&psc=1

★ Site -[OpenCV-How to use cv2.LUT, gamma correction, negative / positive inversion, posterization] [1] [1]:https://pystyle.info/opencv-tone-transform/#outline__6 ・ [How to use digitize (numpy)] [2] [2]:http://arduinopid.web.fc2.com/Q3-36.html