Simple Histogram Equalization

Histogram equalization is a technique used to enhance the global contrast of an image. It works by redistributing the intensity values so that they span the entire possible range (0 to 255 in 8-bit images). This is especially useful for images that are too dark or too bright, as it makes features more visible by equalizing the histogram of pixel intensities.

• cv2.equalizeHist(image)

  • image: input grayscale image (must be single-channel);

  • Returns a new image with enhanced contrast by stretching and flattening the histogram.

Adaptive Histogram Equalization (CLAHE)

CLAHE (Contrast Limited Adaptive Histogram Equalization) is an advanced version of histogram equalization that operates on small regions (tiles) of the image rather than the whole image. It enhances local contrast and avoids over-amplifying noise by limiting the histogram contrast within each tile.

• cv2.createCLAHE(...) creates a CLAHE object with:

  • clipLimit: threshold for contrast limiting (higher value = more contrast);

  • tileGridSize: size of the grid for dividing the image into tiles (e.g., 8x8).

• clahe.apply(image) applies CLAHE to the input image.