Various techniques are disclosed to effectively suppress noise in images (e.g., video or still images). For example, noise in images may be more accurately modeled as having a structured random noise component and a structured fixed pattern noise (FPN) component. Various parameters of noise may be estimated robustly and efficiently in real time and in offline processing. Noise in images may be filtered adaptively, based on various noise parameters and motion parameters. Such filtering techniques may effectively suppress noise even in images that have a prominent FPN component, and may also improve effectiveness of other operations that may be affected by noise.