Subsample artefact

test.py

import math
import numpy
import imageio
from matplotlib import pyplot


def resize(img, size):
  (width, height) = size
  resized = []
  wratio = len(img[0]) / width
  hratio = len(img) / height
  for i in range(height):
    resized.append([])
    for j in range(width):
      resized[i].append(img[math.floor(i * hratio)][math.floor(j * wratio)])
  return resized


def subsample(img, startX, startY, step):
  width = len(img[0])
  height = len(img)
  resized = []
  for i in range(math.floor(height / step)):
    resized.append([])
    for j in range(math.floor(width / step)):
      resized[i].append(img[math.floor(i * step + startX)][math.floor(j * step + startY)])
  return resized


def merge(img, subsample, startX, startY, step):
  width = len(img[0])
  height = len(img)
  for i in range(math.floor(height / step)):
    for j in range(math.floor(width / step)):
      img[i * step + startX][j * step + startY] = subsample[i][j]
  return img

# img = [
#  [1, 0, 0, 1],
#  [0, 0, 0, 0],
#  [0, 0, 0, 0],
#  [1, 0, 0, 1],
# ]


im = imageio.imread('lena.png')
original_width = len(im[0])
original_height = len(im)
print(f'{original_width}x{original_height}')

# Convert to grayscale
img = [[math.floor(0.299 * p[0] + 0.587 * p[1] + 0.114 * p[2]) for p in row] for row in im]

subsampled0 = subsample(img, 0, 0, 2)
imageio.imwrite('subsampled0.png', numpy.asarray(subsampled0))
reconstructed = resize(subsampled0, (original_width, original_height))
imageio.imwrite('subsampled0_resized.png', numpy.asarray(reconstructed))

reconstructed = merge(reconstructed, subsample(img, 1, 1, 2), 1, 1, 2)
imageio.imwrite('merged_with_subsample1.png', numpy.asarray(reconstructed))
reconstructed = merge(reconstructed, subsample(img, 1, 0, 2), 1, 0, 2)
imageio.imwrite('merged_with_subsample2.png', numpy.asarray(reconstructed))
reconstructed = merge(reconstructed, subsample(img, 1, 0, 2), 1, 0, 2)
imageio.imwrite('merged_with_subsample3.png', numpy.asarray(reconstructed))

# [print(row) for row in subsampled0]

# pyplot.imshow(reconstructed, cmap='gray')
# pyplot.show()