Method for removing camera spot noise

Abstract

The present invention discloses a method for effectively removing camera speckle noise suitable for hardware realization, wherein 3*3 window data in the image is obtained by a definite step length, and the window data is wave filtered in four directions of horizon, verticality, diagonal downward, and diagonal upward; slight difference between the pixel value of the center pixel piont and the pixel value of 8 adjacent pixel points are specifically analyzed, and then the relative darker points and lighter pixel points are respectively filtered ; even treating pictures rich in detail, the edge and detail information of the picture can be still effectively protected; while wave filtering operation only contains comparison and signed magnitude arithmetic, which is simply to calculate and much suitable for hardware realization. The method provided by the present invention can rapidly and effectively reduce speckle noise produced in camera, and has no ambiguity in detail. The treated picturenoise can essentially be inhibited and the visual effect is good.

Description

technical field [0001] The invention relates to an image processing method, in particular to a method for removing image noise. Background technique [0002] At present, the application of image processing in chip design is more and more extensive, such as: digital camera, digital video camera, mobile phone, video conferencing system and so on. Image processing generally includes preprocessing, compression, and postprocessing. Video image denoising is an important part of preprocessing. [0003] Video acquisition equipment such as ordinary cameras adopts CMOS (Complementary Metal Oxide Semiconductor) photoreceptors due to the consideration of low power consumption and low cost requirements, which have disadvantages in resolution, dynamic range and noise. insufficient. In a low-light environment, the photosensitive device receives light for a long time and is affected by white noise and dark current. The source video image collected and output is prone to random noise. ...

AI Technical Summary

Problems solved by technology

Although median filtering can retain certain edge and detail information, since the statistical characteristics of the image are not required in the actual operation process, all pixels are filtered in the same way, and some details are more, especially point, line, and peak details. More images will also cause a certain loss of detail

At the same time, median filtering and weighted median filtering need to sort the window data, requiring too many comparison operations, especially when the window is large or weighted median filtering is used, the sorting calculation is relatively large, which is not suitable for hardware implementation

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