Max Denoise Instant
return np.clip(denoised, 0, 1) if name == " main ": import matplotlib.pyplot as plt from skimage import data, img_as_float
# Apply maximal denoising denoised = max_denoise(noisy, sigma=0.2, h=1.5) max denoise
# 2. Wavelet hard thresholding (removes residual high-frequency noise) coeffs = pywt.wavedec2(denoised, wavelet, level=4) if denoised.ndim == 2 else \ pywt.wavedec(denoised, wavelet, level=4) return np
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) 1] range if image.max() >