Bit Planes Io -

The next time you look at a JPEG, remember: beneath that smooth surface lie eight ghosts of information, each holding a different piece of the truth. Have you used bit plane decomposition in a project? Exploring the LSB plane might reveal more than you ever expected.

In the age of high-definition video and terabyte-sized images, it is easy to forget that every digital picture is, at its core, just a collection of numbers. The concept of bit planes offers a fascinating way to peel back the layers of an image, revealing hidden structures, enabling advanced compression, and even uncovering steganographic secrets. bit planes io

import cv2 import numpy as np image = cv2.imread('input.jpg', cv2.IMREAD_GRAYSCALE) Create an empty list to store planes planes = [] Extract each bit plane (0 to 7) for bit in range(8): # Isolate the current bit plane = (image >> bit) & 1 # Scale to 255 for visibility (binary image) plane_visible = plane * 255 planes.append(plane_visible) Save each plane as a separate file for i, plane in enumerate(planes): cv2.imwrite(f'bit_plane_{i}.png', plane) The next time you look at a JPEG,