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US 9,071,733 B2Granted
Method for reducing image or video noise
AssigneeValorbec Societe en Commandite
InventorsEva Rifkah, Aishy Amer
Life of this patent
Estimating the term…
Abstract
There is described a Minimal Iterativity Anisotropic Diffusion (MIAD) approach that estimates the required number of iterations N as a function of the image structure-under-noise ρ and the bound of the noise η. The time step λ is related to the image structure-under-noise ρ and to the bound of noise λ. The stopping time is calculated using T=λ·N, and the edge strength σ is determined as a function of T, η, and ρ.
Claims20
A method for reducing noise in an image/video frame, comprising:
- receiving an input image/video frame and a corresponding noise level η;
- determining a structure-under-noise estimator ρ as a function of a ratio between the noise level η and a structure measure parameter for the input image/video frame;
- determining a number of iterations N and a time step parameter λ from the structure-under-noise estimator ρ;
- determining a stopping time parameter T from the number of iterations N and the time step parameter λ;
- determining an edge strength parameter σ from the time step parameter λ, the noise level η, and the stopping time parameter T using:
- σ
- =
- 1
- T
- ·
- η
- +
- λ
- max
-
-
- ρ
- ·
- 1
- T
- ·
- η
- .
- ;
- denoising the input image/video frame by applying anisotropic diffusion thereto using the edge strength parameter σ, the time step parameter λ, and the number of iterations N, thereby obtaining a denoised image;
- and
- outputting the denoised image.
24 more elements
A system for reducing noise in an image/video frame having a corresponding noise level η, the system comprising:
- a memory;
- a processor coupled to the memory;
- a parameter determining module stored on the memory and executable by the processor, the parameter determining module having program code that when executed, determines a structure-under-noise estimator ρ as a function of a ratio between the noise level η and a structure measure parameter for the input image/video frame, determines a number of iterations N and a time step parameter λ from the structure-under-noise estimator ρ;
- determines a stopping time parameter T from the number of iterations N and the time step parameter λ, and determines an edge strength parameter σ from the time step parameter λ, the noise level η, and the stopping time parameter T using;
- σ
- =
- 1
- T
- ·
- η
- +
- λ
- max
-
-
- ρ
- ·
- 1
- T
- ·
- η
- .
- ;
- and
- a noise reduction module stored on the memory and executable by the processor, the noise reduction module having program code that when executed, denoises the input image/video frame by applying anisotropic diffusion thereto using the edge strength parameter σ, the time step parameter λ, and the number of iterations N, thereby obtaining a denoised image, and outputs the denoised image.
22 more elements
Dependencies are inferred from the claim text.