Max Denoise !!link!! May 2026

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

if denoised.ndim == 2: coeffs = list(coeffs) coeffs[1:] = threshold_coeffs(coeffs[1:], threshold) denoised = pywt.waverec2(coeffs, wavelet) else: coeffs = list(coeffs) coeffs[1:] = threshold_coeffs(coeffs[1:], threshold) denoised = pywt.waverec(coeffs, wavelet) max denoise

# 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 threshold) denoised = pywt.waverec2(coeffs

Parameters: - image: numpy array (grayscale or color) normalized to [0,1] or [0,255] - sigma: estimated noise standard deviation (used for wavelet threshold) - h: non-local means filter strength (larger = stronger denoising) - wavelet: wavelet type for thresholding threshold) denoised = pywt.waverec(coeffs

# 3. Strong Bilateral filter (smooths while keeping edges) denoised = denoise_bilateral(denoised, sigma_color=0.3, sigma_spatial=5, multichannel=(image.ndim==3))