CN107967668B - Image processing method and device - Google Patents
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- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
- G06T3/4015—Image demosaicing, e.g. colour filter arrays [CFA] or Bayer patterns
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- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
- G06T3/4023—Scaling of whole images or parts thereof, e.g. expanding or contracting based on decimating pixels or lines of pixels; based on inserting pixels or lines of pixels
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- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
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Abstract
The invention discloses an image processing method and device, wherein the method comprises the following steps: collecting an RGBIR mosaic image by using an image sensor in an RGBIR format; demosaicing the RGBIR mosaic image to obtain a full-breadth RGBIR image; performing color recovery according to the IR component values in the full-format RGBIR image and the photosensitive characteristic of the image sensor, and eliminating R, G, B infrared light information in the component image; carrying out white balance processing and color correction processing on the image subjected to infrared elimination; performing color space transformation on the image subjected to color correction processing to obtain a YUV domain image; downsampling the YUV domain image to obtain a mosaic image of a YUV domain; performing time domain noise reduction and spatial domain noise reduction on the YUV mosaic image; interpolation calculation is carried out on the image after noise reduction to obtain a full-breadth YUV image, and processing from the RGBIR mosaic image to the YUV image is realized through the method and the device.
Description
Technical Field
The present invention relates to the field of image processing technologies, and in particular, to an image processing method and apparatus based on an rgbiir format.
Background
Rgbiir is a new arrangement of image sensor Color filters, different from the commonly used Bayer format Color Filter Array (CFA), which generally has two arrangements: an image array composed of a 2 × 2 color filter arrangement, as shown in fig. 1, a Red channel (R), a green channel (G), a blue channel (B), an infrared channel (Infra Red, IR), have the same quarter of an image sampling rate; another is an image array composed of a 4 x 4 arrangement of color filters, as shown in fig. 2, where the green channel G has one-half image sampling rate, the infrared channel IR has one-fourth image sampling rate, the red channel R and the blue channel B each have one-eighth image sampling rate, the RGB channels in the RGB color filter array can sense both visible light and invisible infrared light, and the IR channels can sense both visible light when sensing invisible infrared light.
Because of the different arrangement modes of the filters and the different light sensing modes, the image processing system of the image sensor based on the rgb ir color filter cannot directly use the image processing method and apparatus based on the Bayer color filter, and therefore, it is necessary to provide a technical means for performing image processing on the image data based on the rgbiir format to obtain a normally colored YUV image which can be subsequently processed, stored or displayed.
Disclosure of Invention
In order to overcome the defects of the prior art, the present invention provides an image processing method and an image processing apparatus, which can process the collected rgbiir mosaic image data through a series of images to obtain a normally colored YUV image for subsequent processing, storage or display.
To achieve the above and other objects, the present invention provides an image processing method, comprising:
collecting an RGBIR mosaic image by using an image sensor in an RGBIR format;
step two, performing demosaicing treatment on the obtained RGBIR mosaic image to obtain a full-breadth RGBIR image;
thirdly, color recovery is carried out according to the IR component values in the obtained full-breadth RGBIR image and the photosensitive characteristic of the image sensor, and infrared light information in R, G, B component images is eliminated;
step four, white balance processing and color correction processing are carried out on the image after infrared elimination;
fifthly, performing color space transformation on the image after color correction processing to obtain a YUV domain image;
step six, downsampling the acquired YUV domain image to obtain a mosaic image of a YUV domain;
seventhly, performing time domain noise reduction and space domain noise reduction on the acquired YUV mosaic image;
and step eight, performing interpolation calculation on the denoised YUV domain mosaic image to obtain a full-breadth YUV image.
Further, in the first step, an rgbiir mosaic image with a 4 × 4 format is acquired by an rgbiir image sensor with a 4 × 4 filter arrangement; or collecting RGBIR mosaic images with a 2 x 2 format by an RGBIR image sensor with a 2 x 2 filter arrangement mode.
Further, in the second step, a boundary preservation method is adopted, the G channel is interpolated to obtain a full-format G component image, and then the difference value between the G channel and other channels is used to interpolate other channel values to obtain a full-format R, G, B, IR component image.
Further, in step three, after the R, G, B, IR component image of the full breadth is obtained by interpolation in step two, the ratio of the IR component in the current R, G, B component image and the mutual influence between R, G, B components are calculated according to the IR component value of the current pixel and the photosensitive characteristic of the image sensor, so as to eliminate the infrared information in the R, G, B component image.
Further, in step seven, the obtained YUV domain mosaic image subchannels are subjected to boundary-preserving spatial domain noise reduction and motion-preserving temporal domain noise reduction.
Further, in the eighth step, an interpolation algorithm of boundary reservation is adopted for performing interpolation calculation on the YUV mosaic image.
To achieve the above object, the present invention also provides an image processing apparatus comprising:
the image acquisition unit is used for acquiring an RGBIR mosaic image by using an image sensor in an RGBIR format;
the RGBIR image demosaicing unit is used for demosaicing the obtained RGBIR mosaic image to obtain a full-breadth RGBIR image;
the color recovery unit is used for carrying out color recovery according to the obtained IR component values in the full-breadth RGBIR image and the photosensitive characteristic of the image sensor, and eliminating R, G, B infrared light information in the component image;
the color processing unit is used for carrying out white balance processing and color correction processing on the image subjected to infrared elimination;
the color space transformation unit is used for performing color space transformation on the image after the color correction processing to obtain a YUV domain image;
the image downsampling unit is used for downsampling the acquired YUV domain image to obtain a mosaic image of a YUV domain;
the image denoising unit is used for performing time domain denoising and space domain denoising processing on the acquired YUV mosaic image;
and the image interpolation unit is used for carrying out interpolation calculation on the denoised YUV domain mosaic image to obtain a full-breadth YUV image.
Further, the RGBIR image demosaicing unit adopts a boundary retention method, firstly interpolates a G channel to obtain a full-format G component image, and then interpolates other channel values by using the difference value of the G channel and other channels to obtain a full-format R, G, B, IR component image.
Further, after the color recovery unit obtains the R, G, B, IR component image of the full width, the color recovery unit calculates the ratio of the IR components in the current R, G, B component image and the mutual influence between the R, G, B components according to the IR component value of the current pixel and the photosensitive characteristic of the image sensor, so as to eliminate the infrared information in the R, G, B component image.
Further, the image denoising unit performs boundary-preserving spatial domain denoising and motion-preserving temporal domain denoising on the acquired YUV domain mosaic image subchannels.
Compared with the prior art, the invention realizes the image processing method and device based on the RGBIR format, and the collected RGBIR mosaic image data is processed through a series of images to obtain the normal-color YUV image which can be subsequently processed, stored or displayed.
Drawings
FIG. 1 is a schematic diagram of a prior art 2 × 2RGBIR image format;
FIG. 2 is a diagram of a 4 × 4RGBIR image format according to the prior art;
FIG. 3 is a flow chart illustrating steps of an image processing method according to the present invention;
fig. 4 is a schematic diagram of a YUV mosaic image according to an embodiment of the present invention;
fig. 5 is a system architecture diagram of an image processing apparatus according to the present invention.
Detailed Description
Other advantages and capabilities of the present invention will be readily apparent to those skilled in the art from the present disclosure by describing the embodiments of the present invention with specific embodiments thereof in conjunction with the accompanying drawings. The invention is capable of other and different embodiments and its several details are capable of modification in various other respects, all without departing from the spirit and scope of the present invention.
An image sensor using a color filter array of the RGBIR acquires a mosaic image. The missing color components must be subsequently recovered from the mosaic image by image processing techniques to obtain a full-width RGBIR image. Since the full-format RGB image contains invisible infrared light components, the real colors of RGB must be recovered using the infrared channel IR. Since the subsequent image processing of the full-format RGB image results in a large hardware overhead of line cache and a hardware overhead of frame cache, the color-recovered RGB image needs to be subjected to mosaic processing (down-sampling processing) and then to subsequent image processing.
FIG. 3 is a flowchart illustrating steps of an image processing method according to the present invention. As shown in fig. 3, an image processing method of the present invention includes the steps of:
And step 303, performing color recovery according to the obtained IR component values in the full-format RGBIR image and the photosensitive characteristic of the image sensor, and eliminating R, G, B infrared light information in the component image. Specifically, after the R, G, B, IR full-width component image is obtained by interpolation according to the step 302, the mutual influence between the IR proportion in the current R, G, B component image and the R, G, B component can be calculated according to the IR component value of the current pixel and the photosensitive characteristic of the image sensor, and the infrared light information in the R, G, B component image is eliminated by using a color recovery calculation formula, which is shown in the following formula (1), wherein each parameter variable has different values according to different RGBIR sensors.
And step 304, performing white balance processing and color correction processing on the image after infrared elimination. In the embodiment of the present invention, after performing infrared elimination on the full-width rgbiir image according to step 303, white balance processing is performed on the image after infrared elimination, and then color correction processing is performed on the image after white balance processing, so that the color is closer to reality.
And 305, performing color space transformation on the image after the color correction processing to obtain a YUV domain image. Specifically, in step 305, the RGB image is transformed into a YUV color space image.
And step 306, downsampling the acquired YUV domain image to obtain a mosaic image of a YUV domain. In an embodiment of the present invention, the YUV image is downsampled to obtain a YUV mosaic image in a 2 × 2 format, as shown in fig. 4, having four sampling modes, wherein the Y component has a half sampling rate and the U, V component has a quarter sampling rate.
And 307, performing time domain noise reduction and space domain noise reduction on the acquired YUV mosaic image. Specifically, the step performs boundary-preserving spatial domain noise reduction and motion-preserving time domain noise reduction on the YUV domain mosaic image subchannels to obtain a high-subjective-quality image.
And 308, performing interpolation calculation on the denoised YUV domain mosaic image to obtain a full-width YUV image. In the embodiment of the invention, interpolation calculation is carried out on the YUV mosaic image, and a relatively complex interpolation algorithm with boundary retention is adopted to obtain a full-breadth YUV image.
Fig. 5 is a system architecture diagram of an image processing apparatus according to the present invention, as shown in fig. 5, the image processing apparatus according to the present invention includes: the system comprises an image acquisition unit 501, an RGBIR image demosaicing unit 502, a color recovery unit 503, a color processing unit 504, a color space conversion unit 505, an image downsampling unit 506, an image denoising unit 507, an image interpolation unit 508 and an image output unit 509.
The image acquisition unit 501 acquires an rgbiir mosaic image using an image sensor of an rgbiir format. Specifically, the image acquisition unit 301 acquires an rgbiir mosaic image in a 4 × 4 format by using an rgbiir image sensor in a 4 × 4 filter arrangement; or collecting RGBIR mosaic images with a 2 x 2 format by an RGBIR image sensor with a 2 x 2 filter arrangement mode.
The rgbiir image demosaicing unit 502 is configured to perform demosaicing on the obtained rgbiir mosaic image to obtain a full-width rgbiir image. In the embodiment of the present invention, the rgbiir image demosaicing unit 502 uses an 11 × 11 data window, and uses a boundary reservation method to interpolate a G channel to obtain a full-width G component image; and then, the difference value of the G channel and other channels is utilized to interpolate other channel values to obtain R, G, B, IR component images of the full breadth.
And a color recovery unit 503, configured to perform color recovery according to the obtained IR component values in the full-width RGBIR image and the photosensitive characteristic of the image sensor, so as to eliminate R, G, B infrared light information in the component image. Specifically, after the rgbiir image demosaicing unit 502 performs interpolation to obtain a full-width R, G, B, IR component image, the color recovery unit 503 obtains the mutual influence between the IR proportion in the current R, G, B component image and the R, G, B component according to the IR component value of the current pixel and the photosensitive characteristic of the image sensor, and eliminates the infrared light information in the R, G, B component image by using a color recovery calculation formula, which is shown below, wherein each parameter variable has different values according to different rgbiir sensors.
A color processing unit 504, configured to perform white balance processing and color correction processing on the image after infrared elimination. In the embodiment of the present invention, after the color recovery unit 503 performs infrared elimination on the full-width rgbiir image, the color processing unit 504 performs white balance processing on the image after infrared elimination, and then performs color correction processing on the image after white balance processing, so that the color is closer to reality.
And a color space transformation unit 505, configured to perform color space transformation on the image after the color correction processing, so as to obtain a YUV domain image. Specifically, the color space conversion unit 505 performs conversion of the RGB image into a YUV color space image on the color correction-processed image.
And an image downsampling unit 506, configured to downsample the obtained YUV domain image to obtain a YUV domain mosaic image. In an embodiment of the present invention, the image downsampling unit 506 downsamples the YUV image to obtain a YUV mosaic image in a 2 × 2 format, and has four sampling modes, wherein the Y component has a half sampling rate and the U, V component has a quarter sampling rate.
And an image denoising unit 507, configured to perform time domain denoising and spatial domain denoising on the obtained YUV mosaic image. Specifically, the image denoising unit 507 performs boundary-preserving spatial domain denoising and motion-preserving temporal domain denoising on the YUV domain mosaic image subchannels to obtain a higher subjective quality image.
And the image interpolation unit 508 is configured to perform interpolation calculation on the denoised YUV domain mosaic image to obtain a full-width YUV image. In the embodiment of the present invention, the image interpolation unit 508 performs interpolation calculation on the YUV mosaic image, and obtains a full-width YUV image by using a more complex interpolation algorithm with boundary preservation.
The image output unit 509 outputs the full-width YUV image after image interpolation for further image processing, image storage processing, or terminal display.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Modifications and variations can be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the present invention. Therefore, the scope of the invention should be determined from the following claims.
Claims (7)
1. An image processing method comprising the steps of:
collecting an RGBIR mosaic image by using an image sensor in an RGBIR format;
step two, performing demosaicing treatment on the obtained RGBIR mosaic image to obtain a full-breadth RGBIR image;
thirdly, color recovery is carried out according to the IR component values in the obtained full-breadth RGBIR image and the photosensitive characteristic of the image sensor, and infrared light information in R, G, B component images is eliminated;
step four, white balance processing and color correction processing are carried out on the image after infrared elimination;
fifthly, performing color space transformation on the image after color correction processing to obtain a YUV domain image;
step six, downsampling the acquired YUV domain image to obtain a mosaic image of a YUV domain;
seventhly, performing time domain noise reduction and space domain noise reduction on the acquired YUV mosaic image;
step eight, performing interpolation calculation on the denoised YUV domain mosaic image to obtain a full-breadth YUV image;
in the second step, a boundary retaining method is adopted, a G channel is interpolated to obtain a full-format G component image, and then other channel values are interpolated by using the difference value between the G channel and other channels to obtain a full-format R, G, B, IR component image;
in the third step, after the R, G, B, IR component image of the full breadth is obtained by interpolation in the second step, the ratio of the IR component in the current R, G, B component image and the mutual influence among R, G, B components are calculated according to the IR component value of the current pixel and the photosensitive characteristic of the image sensor, so as to eliminate the infrared information in the R, G, B component image.
2. An image processing method as claimed in claim 1, characterized by: in the first step, collecting RGBIR mosaic images with 4 x 4 format by an RGBIR image sensor with 4 x 4 filter arrangement mode; or collecting RGBIR mosaic images with a 2 x 2 format by an RGBIR image sensor with a 2 x 2 filter arrangement mode.
3. An image processing method as claimed in claim 1, characterized by: in the seventh step, the obtained YUV domain mosaic image sub-channels are subjected to boundary-preserving spatial domain noise reduction and motion-preserving temporal domain noise reduction.
4. An image processing method as claimed in claim 1, characterized by: and in the step eight, performing interpolation calculation on the YUV mosaic image by adopting an interpolation algorithm of boundary reservation.
5. An image processing apparatus comprising:
the image acquisition unit is used for acquiring an RGBIR mosaic image by using an image sensor in an RGBIR format;
the RGBIR image demosaicing unit is used for demosaicing the obtained RGBIR mosaic image to obtain a full-breadth RGBIR image;
the color recovery unit is used for carrying out color recovery according to the obtained IR component values in the full-breadth RGBIR image and the photosensitive characteristic of the image sensor, and eliminating R, G, B infrared light information in the component image;
the color processing unit is used for carrying out white balance processing and color correction processing on the image subjected to infrared elimination;
the color space transformation unit is used for performing color space transformation on the image after the color correction processing to obtain a YUV domain image;
the image downsampling unit is used for downsampling the acquired YUV domain image to obtain a mosaic image of a YUV domain;
the image denoising unit is used for performing time domain denoising and space domain denoising processing on the acquired YUV mosaic image;
the image interpolation unit is used for carrying out interpolation calculation on the YUV domain mosaic image subjected to noise reduction to obtain a YUV image with a full breadth;
after obtaining the R, G, B, IR component image of the full breadth, the color recovery unit calculates the ratio of the IR component in the current R, G, B component image and the mutual influence between the R, G, B components according to the IR component value of the current pixel and the photosensitive characteristic of the image sensor, so as to eliminate the infrared information in the R, G, B component image.
6. An image processing apparatus according to claim 5, characterized in that: the RGBIR image demosaicing unit adopts a boundary retention method, firstly interpolates a G channel to obtain a full-breadth G component image, and then interpolates other channel values by using the difference value of the G channel and other channels to obtain a full-breadth R, G, B, IR component image.
7. An image processing apparatus according to claim 5, characterized in that: the image denoising unit performs boundary-preserved spatial domain denoising and motion-preserved time domain denoising on the acquired YUV domain mosaic image sub-channels.
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| CN111770246A (en) * | 2019-04-02 | 2020-10-13 | 上海富瀚微电子股份有限公司 | Image noise reduction device and method |
| CN110290370B (en) * | 2019-07-05 | 2020-09-18 | 上海富瀚微电子股份有限公司 | Image processing method and device |
| CN111601046B (en) * | 2020-04-22 | 2022-03-01 | 惠州市德赛西威汽车电子股份有限公司 | Dark light environment driving state monitoring method |
| CN114095672A (en) * | 2020-07-31 | 2022-02-25 | 北京小米移动软件有限公司 | Imaging system, method and electronic device |
| CN112017169A (en) * | 2020-08-25 | 2020-12-01 | 重庆大学 | Processing method of mosaic picture |
| WO2022217525A1 (en) * | 2021-04-15 | 2022-10-20 | 深圳市大疆创新科技有限公司 | Image noise reduction processing method and device, and imaging device |
| CN113781326A (en) * | 2021-08-11 | 2021-12-10 | 北京旷视科技有限公司 | Demosaicing method and device, electronic equipment and storage medium |
| CN114612571B (en) * | 2022-03-07 | 2023-05-23 | 重庆紫光华山智安科技有限公司 | White balance calibration parameter generation and image correction method, system, equipment and medium |
| CN115689887A (en) * | 2022-10-28 | 2023-02-03 | 辉羲智能科技(上海)有限公司 | Automatic driving RGBIR image resampling method, system, terminal and medium |
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