# US 2020/0396356 A1 · Noise estimation using user-configurable information

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- Number: US 2020/0396356 A1
- Document ID: US20200396356A1
- Status: Published application
- Kind: A1
- Application number: 16/442,137
- Filed: 2019-06-14
- Published: 2020-12-17
- Earliest claimed: 2019-06-14
- Assignees: Texas Instmments Incorporated
- Applicants: Texas Instruments Incorporated
- Inventors: Gang HUA; Mihir Narendra MODY; Rajasekhar Reddy ALLU; Niraj NANDAN; Shashank DABRAL
- Web page: https://patentgrep.com/patent/US20200396356A1

## CPC

- H04N 23/81: for suppressing or minimising disturbance in the image signal generation
- H04N 23/84: for processing colour signals
- H04N 25/131: including elements passing infrared wavelengths
- H04N 25/133: including elements passing panchromatic light, e.g. filters passing white light
- H04N 25/135: {based on four or more different wavelength filter elements}
- H04N 25/61: the noise originating only from the lens unit, e.g. flare, shading, vignetting or "cos4"
- G06T 2207/20064: Wavelet transform [DWT]
- H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL

## Abstract

In some examples, a method comprises receiving pixel data from an image capture device having a color filter, wherein the pixel data represents a portion of an image. The method further includes performing wavelet decomposition on the pixel data to produce decomposed pixel data and determining a local intensity of the pixel data. The method also includes determining a noise threshold value based on the local intensity and a noise intensity function that is based on the color filter; determining a noise value for the pixel data based on the decomposed pixel data and the noise threshold value; and correcting the pixel data based on the noise value to produce an output image.

## Claims

### Claim 1

A method comprising:
receiving pixel data from an image capture device having a color filter, wherein the pixel data represents a portion of an image;
performing wavelet decomposition on the pixel data to produce decomposed pixel data;
determining a local intensity of the pixel data;
determining a noise threshold value based on the local intensity and a noise intensity function that is based on the color filter;
determining a noise value for the pixel data based on the decomposed pixel data and the noise threshold value; and
correcting the pixel data based on the noise value to produce an output image.

### Claim 2 (depends on 1)

The method of claim 1 further comprising:
receiving correlation information for the color filter that includes a set of averaging weights, wherein the determining of the local intensity applies the set of averaging weights of the correlation information to the pixel data to determine the local intensity.

### Claim 3 (depends on 2)

The method of claim 2, wherein the determining of the noise value includes:
averaging the decomposed pixel data using the set of averaging weights to determine an average of the decomposed pixel data; and
dividing the average of the decomposed pixel data by the noise threshold value.

### Claim 4 (depends on 1)

The method of claim 1 further comprising:
determining a gain based on a location, within the image, of the portion of the image associated with the pixel data;
wherein the determining of the noise threshold value includes applying an inverse of the gain to the local intensity and applying the gain to the noise threshold value prior to the determining of the noise value for the pixel data based on the noise threshold value.

### Claim 5 (depends on 1)

The method of claim 1 further comprising generating a gain value and an inverse of the gain value by a lens shading correction compensation logic present in the noise filter.

### Claim 6 (depends on 1)

The method of claim 1, wherein the noise-intensity function is a piecewise linear function.

### Claim 7 (depends on 1)

The method of claim 1, wherein the user-defined noise-intensity function is based on a 2×2 pattern of the color filter array.

### Claim 8

A system, comprising:
an image capture device configured to capture raw pixel data of multiple images of a scene; and
an image processor coupled to the image capture device, the image processor comprising:
noise filter logic configured to generate a signal to noise ratio value using a fixed-bit size raw pixel data and a user-defined noise-intensity function, the fixed-bit size raw pixel data comprising merged raw pixel data of the multiple images,
wherein the noise filter logic comprises suppression logic that is configured to estimate noise in the multiple images using the signal to noise ratio value.

### Claim 9 (depends on 8)

The system of claim 8, wherein the image processor is programmable with coordinates of an optical center of the image capture device.

### Claim 10 (depends on 8)

The system of claim 8, wherein the suppression logic is configured to implement a piece-wise linear function to estimate the noise.

### Claim 11 (depends on 8)

The system of claim 8, wherein the noise filter logic comprises:
lens shading correction compensation logic configured to compute a gain value based on user-defined coordinates of an optical center of the image capture device and a user-defined approximation logic.

### Claim 12 (depends on 8)

The system of claim 8, wherein the noise filter logic comprises averaging logic configured to generate correlated local intensity of the multiple images based on user-programmed correlation information of a color filter array employed in the image capture device.

### Claim 13 (depends on 12)

The system of claim 12, wherein the user-defined noise-intensity function is based on a 2×2 pattern of the color filter array.

### Claim 14 (depends on 8)

The system of claim 8, wherein the user-defined noise-intensity function is a piecewise linear function.

### Claim 15

An image processing system, comprising:
an image capture device configured to capture multiple images of raw pixel data of a scene; and
an image processor coupled to the image capture device, comprising:
first averaging logic configured to generate correlated local intensity of the multiple images based on a user-programmed correlation information of a color filter array employed in the image capture device;
noise calculation logic configured to generate a noise threshold value based on the correlated local intensity and a user-defined first approximation logic; and
sub-band suppression logic configured to estimate noise in the multiple images using the noise threshold value.

### Claim 16 (depends on 15)

The image processing system of claim 15, further comprising lens shading correction compensation logic configured to compute a gain value and an inverse of the gain value based on a user-defined coordinates of an optical center of the image capture device and a user-defined second approximation logic.

### Claim 17 (depends on 16)

The image processing system of claim 16, wherein the user-defined second approximation logic implements a piecewise linear function.

### Claim 18 (depends on 15)

The image processing system of claim 15, wherein the sub-band suppression logic further comprises a second averaging logic configured to generate a correlated logical signal value of the multiple images based on the user-programmed correlation information of a color filter array employed in the image capture device.

### Claim 19 (depends on 18)

The image processing system of claim 18, the user-programmed correlation information is based on a 2×2 pattern of the color filter array.

### Claim 20 (depends on 15)

The image processing system of claim 15, wherein the user-defined first approximation logic implements a piecewise linear function.