Image filtering method and apparatus

Abstract

The invention relates to the technical field of communication electronics, in particular to an image filtering method and apparatus. The method comprises the steps of judging whether a pixel point is a boundary pixel point or not, and if not, taking the pixel point as a central point; selecting a reference matrix of the central point in a preset mode; calculating the value of a to-be-interpolated region in the reference matrix, wherein the to-be-interpolated region is next to a pixel central point; and calculating the value of the pixel central point according to the value of the to-be-interpolated region, and replacing the value of the pixel central point. According to the image filtering method and apparatus, denoising is performed for a bayer image; filtering is performed without destroying original noise characteristics of the bayer image; and pixel value interpolation is performed, so that the pixel information amount of the bayer image is increased, the noises can be effectively removed, the denoising reliability can be ensured, and hardware implementation is facilitated.

Description

technical field [0001] The invention relates to the technical field of communication electronics, in particular to an image filtering method and device thereof. Background technique [0002] The pictures inside the camera are raw pictures saved in bayer format and stored in .raw format, which is an unprocessed and uncompressed format. The bayer format is stored in three different channels: R, G, and B. The storage format is as follows: figure 1 shown. [0003] The image is collected and stored by the CMOS sensor, and the reception of image information will be hindered due to external interference and noise generated by optoelectronic equipment and circuits. Therefore, denoising processing is required, and the currently commonly used denoising methods are as follows: [0004] General denoising is based on grayscale images or RGB single-channel filtering operations, each pixel is a true representation of a pixel, and the amount of information that can be obtained for a baye...

AI Technical Summary

Problems solved by technology

When the image is converted from bayer format to RGB format, an interpolation algorithm is required. Image interpolation will destroy the characteristics of the image itself and generate new noise.

Before interpolation, there are still some algorithms that will destroy the structure of the image itself, increase and increase the noise of the image, and increase the difficulty of image denoising

[0006] The ordinary bayer image denoising has only 1 / 4 of the information of the gray image, and the pixel value can only be extracted interlaced in the pixel extraction. When the window is small, it is difficult to extract a large amount of information of the same channel, so It brings great difficulty to filtering and greatly reduces the accuracy of filtering

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