Interpolating method and apparatus of Bayer-format images

An interpolation method and interpolation technology, applied in the field of image processing, can solve the problems of false color and border aliasing effect, affecting image quality, etc., to achieve the effect of improving aliasing effect, improving image quality, and reducing impact

Inactive Publication Date: 2017-05-24
X CHIP MICROELECTRONICS TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The embodiment of the present invention provides a Bayer format image interpolation method and device to solve the problem that the interpolation method in the prior art causes false colors and border jagged effects, thus affecting the image quality

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  • Interpolating method and apparatus of Bayer-format images
  • Interpolating method and apparatus of Bayer-format images
  • Interpolating method and apparatus of Bayer-format images

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Embodiment 1

[0023] figure 1 This is a flowchart of the method for interpolation of Bayer format images provided by the first embodiment of the present invention. This embodiment is applicable to interpolation processing on Bayer format images. The method can be executed by an interpolation device for Bayer format images, which can use software. And / or hardware. Such as figure 1 As shown, the method of Embodiment 1 of the present invention specifically includes:

[0024] S101: Detect noise pixels in the image to be processed, and remove the detected noise pixels to obtain a denoised image.

[0025] As we all know, the sampling of an image usually has a uniform sampling frequency. The higher the sampling frequency, the higher the definition of the image. However, the respective image content of each image may include areas with rich details, and if a uniform sampling frequency is used, the non-detailed areas in the image may be clear, but these areas with rich details are still unclear. Then, i...

Embodiment 2

[0034] figure 2 This is a flowchart of the interpolation method for a bayer format image provided in the second embodiment of the present invention. The second embodiment further explains the operations in the first embodiment on the basis of the first embodiment. Such as figure 2 As shown, the method of Embodiment 2 of the present invention specifically includes:

[0035] S201: Detect noise pixels in the image to be processed, and remove the detected noise pixels to obtain a denoised image.

[0036] Among them, detecting noise pixels in the image to be processed and removing the detected noise pixels includes:

[0037] Use S-ROD algorithm to detect noise pixels in the image to be processed;

[0038] Perform the following processing on the detected noise pixels in turn to obtain a denoised image: replace the pixel value of the current noise pixel with the pixel in the preset adjacent area that has the same channel as the current noise pixel The mean of the values.

[0039] Specifica...

Embodiment 3

[0079] The third embodiment of the present invention provides an interpolation method for a bayer format image. On the basis of the foregoing embodiment, the third embodiment illustrates the operation flow of the interpolation method as an example. Such as Figure 5 As shown, the interpolation method of this embodiment includes:

[0080] S301. Use S-ROS algorithm to monitor noise;

[0081] S302: Determine whether there is a noise pixel value, that is, whether a pixel value that meets the characteristics of the noise pixel point is detected, and when it is judged to be yes, execute step S303, otherwise, execute step S305;

[0082] S303. Eliminate pixel values ​​containing noise.

[0083] S304: Replace the noise pixel value by using the average value of the same channel pixel value in the neighborhood;

[0084] S305. Calculate the respective weights of pixels used for green channel interpolation. In this embodiment, the green channel is used as a highly sensitive channel;

[0085] S306: I...

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Abstract

The embodiments of the present invention disclose an interpolating method and apparatus of Bayer-format images. The method includes the following steps that: noise pixels in an image to be processed are detected, and the detected noise pixels are removed, so that a denoised image can be obtained; the interpolation weights of pixels in the denoised image which are used for high-sensitivity channel interpolation are calculated according to a preset interpolation template, and interpolation is performed on a high-sensitivity channel in the denoised image according to the interpolation weights and the pixel values of the corresponding pixels, and a high-sensitivity channel interpolated image can be obtained; and interpolation is performed on low-sensitivity channels in the high-sensitivity channel interpolated image through using guided filtering, so that an interpolation result image of the image to be processed is obtained. According to the interpolating method and apparatus of the Bayer-format images provided by the embodiments of the invention, the noise pixels are removed, the reliability and accuracy of interpolation input data are improved, influence on an interpolation result caused by possible noises can be decreased; and correlation among the three channels of data is improved through the guided filtering method, and therefore, the sawtooth effect of image borders can be improved, and image quality can be improved.

Description

Technical field [0001] The embodiments of the present invention relate to image processing technology, and in particular, to an interpolation method and device for Bayer format images. Background technique [0002] In digital color imaging, the most commonly used sensors include CCD (charge coupled device) sensors and CMOS (complementary metal oxide semiconductor) sensors. The photosensitive surface of these two types of sensors is covered with a color filter array. (CFA, color filter array), due to design process limitations, CFA only allows each pixel of the sensor to record the value of one color channel, and the image obtained by this sensor is called a Bayer format image. [0003] Since each pixel of the Bayer format image can only directly obtain one of the three color channels, it is necessary to estimate the missing channel of each pixel through a certain interpolation method, so that each pixel contains, for example, red (R ), green (G), blue (B) three color channels to f...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N9/04H04N9/64
CPCH04N9/64H04N23/10
Inventor 张然然
Owner X CHIP MICROELECTRONICS TECH CO LTD
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