Max Denoise May 2026

# Add strong synthetic noise noisy = random_noise(original, mode='gaussian', var=0.04) noisy = random_noise(noisy, mode='s&p', amount=0.05) # extra salt & pepper

# Apply maximal denoising denoised = max_denoise(noisy, sigma=0.2, h=1.5) max denoise

Returns: - denoised: maximally denoised image """ # Ensure float in [0,1] range if image.max() > 1.0: image = image.astype(np.float32) / 255.0 else: image = image.astype(np.float32) # Add strong synthetic noise noisy = random_noise(original,

import numpy as np import cv2 import pywt from skimage.restoration import denoise_nl_means, denoise_bilateral from skimage.util import random_noise def max_denoise(image, sigma=0.1, h=1.15, wavelet='db8'): """ Apply maximum-strength denoising using a cascade of methods. var=0.04) noisy = random_noise(noisy

# 4. Median filter (removes any remaining salt-and-pepper noise) denoised = cv2.medianBlur((denoised * 255).astype(np.uint8), 3).astype(np.float32) / 255.0

# Load a test image original = img_as_float(data.camera())