US 7,418,149 B2Granted

Apparatus and method for adaptive 3D noise reduction

AssigneeAlgolith Inc.

InventorsChon Tam Le Dinh, Duong Tuan Nguyen, Thi Thanh Hien Nguyen

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Abstract

A non-iterative 3D processing method and system is disclosed for generic noise reduction. The 3D noise reducer is based on a simple conversion of the five types of noise to equivalent additive noise of varying statistics. The proposed technique comprises also an efficient temporal filtering technique which combines Minimization of Output Noise Variance (MNV) and Embedded Motion Estimation (EME). The proposed temporal filtering technique may be furthermore combined with classical motion estimation and motion compensation for more efficient noise reducer. The proposed technique comprises also a spatial noise reducer which combines Minimum Mean Squared Error (MMSE) with robust and effective shape adaptive windowing (SAW) is utilized for smoothing random noise in the whole image, particularly for edge regions. Another modification to MMSE is also introduced for handling banding effect for eventual excessive filtering in slowly varying regions.

Claims14

Dependent claims

An apparatus for reducing multiple noise types in a video input signal, said apparatus comprising:

a noise power converter for receiving and using said video input signal, a variance of additive noise, a variance of multiplicative noise and an indication of a type of noise for estimating an equivalent additive noise variance signal;
a temporal recursive filter using said equivalent additive noise variance and said video input signal for generating a temporally filtered video signal and a residual noise variance signal;
a spatial noise reducer using said residual noise variance signal and said temporally filtered video signal for spatially filtering said video input signal to provide a video output signal having reduced noise;
and
wherein said noise power converter comprises a low pass filter for filtering said video input signal to provide a low pass filtered signal;
a shape adaptive window for receiving and using said low pass filtered signal, and a given threshold tolerance for calculating a binary signal ωij(c,r) representing local classification results within said threshold tolerance and a signal N(c,r) indicative of similar pixels in said window;
a shape adaptive window mean estimator using said binary signal ωij(c,r), said N(c,r) signal and said video input signal for calculating a local estimated means signal value μY(c,r) given by
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and
an equivalent additive noise variance calculator using said local estimated means signal value μY(c,r), said variance of additive noise, said variance of multiplicative noise and said indication of a type of noise for calculating said equivalent additive noise variance signal.

51 more elements

A method for reducing multiple noise types in a video input signal, said method comprising:

estimating an equivalent additive noise variance signal using said video input signal, a variance of additive noise, a variance of multiplicative noise and an indication of a type of noise;
temporally filtering said video input signal video signal
generating a residual noise variance signal using said equivalent additive noise variance and said video input signal;
spatially filtering said temporally filtered video signal using said residual noise variance signal and said video input signal to provide a video output signal having reduced noise;
and
wherein said estimating of an equivalent additive noise variance signal comprises low-pass filtering said video input signal to provide a low-pass filtered signal;
calculating a binary signal ωij(c,r) representing local classification results within said threshold tolerance and a signal N(c,r) indicative of similar pixels in said window using said low pass filtered signal, and a given threshold tolerance;
calculating a local estimated means signal value μY(c,r) using said binary signal ωij(c,r), said N(c,r) signal and said video input signal calculating a local estimated means signal value μY(c,r) using
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and calculating said equivalent additive noise variance signal using said local estimated means signal value μY(c,r), said variance of additive noise, said variance of multiplicative noise and said indication of a type of noise.

50 more elements

Dependencies are inferred from the claim text.

Facts

Application: 11/191,919Filed 29 Jul 2005 · us provisional application
Priority: 30 Jul 2004
Published: US 2006/0056724 A116 Mar 2006
Granted: 26 Aug 2008
Term ends: Not estimatedThe source records don’t support an estimate.

Classification16 codes

H04N 5/21
Picture signal circuitry for video frequency region: circuitry for suppressing or minimising disturbance, e.g. moiré or halo
G06T 5/20
Image enhancement or restoration: using local operators
G06T 5/50
Image enhancement or restoration: using two or more images, e.g. averaging or subtraction
G06T 5/70
Image enhancement or restoration: denoising; Smoothing