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A Mesh Noise Removal Method Preserving Sharpness

A technology of noise elimination and grid, applied in image enhancement, image analysis, instruments, etc., can solve the problems of high-speed operation, consumption of large computing resources, insufficiency of image processing speed, etc., to achieve low computing resource requirements and reduce The effect of system resource cost

Active Publication Date: 2020-06-02
BEIJING DAHENG IMAGE VISION +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] In the prior art, there are still some complex algorithms to remove grid noise or perform edge detection in the process of grid noise removal, but the existing grid noise removal or edge detection algorithms will consume a large amount of computing resources, resulting in the loss of image processing. Applications where the speed cannot meet high-speed operation conditions

Method used

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  • A Mesh Noise Removal Method Preserving Sharpness
  • A Mesh Noise Removal Method Preserving Sharpness
  • A Mesh Noise Removal Method Preserving Sharpness

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Embodiment Construction

[0034] The present invention will be described in detail below with reference to the accompanying drawings and the embodiments thereof, but the protection scope of the present invention is not limited to the scope described in the embodiments.

[0035] The present invention adopts 2×2 median filter to carry out non-linear processing on the image, in order to maintain the sharpness of the edge in the scene, the smooth region is judged before filtering, and the median filter is not processed for the non-smooth region.

[0036] 1 Non-smooth region voting (including edge detection process and voting process).

[0037] 1.1 Edge detection

[0038] Edge detection is performed in both horizontal and vertical directions within a 3×3 range on the lower right of the current point.

[0039] like figure 1 As shown, the current point is a.

[0040] The horizontal correlation points are b and c, if (a-b)*(b-c)>0,

[0041] It is determined that there is an edge in the horizontal direction...

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Abstract

The invention discloses a grid noise elimination method that maintains sharpness. The method includes: filtering the smooth area in the target image based on determining whether each pixel in the target image belongs to a smooth area. The present invention adopts the voting method for smooth area screening. Starting from a corner of the image, each pixel is voted on for the smooth area pixel by pixel, and the voting value of the current pixel is assigned to its related pixels to determine the voting value of each pixel. Therefore, grid noise is removed while maintaining image sharpness and noise immunity. The present invention has few parameters, is independent of image brightness, and has good processing effects on images with different grid properties.

Description

technical field [0001] The invention relates to an image quality improvement technology. Aiming at the current optical sensor with grid template noise, the method can remove the grid noise in the image while retaining the sharpness of the edge of the image. Background technique [0002] Grid noise is generated because there are periodic brightness differences in the horizontal and vertical directions of the image, and these differences are specifically manifested as horizontal and vertical stripes. An image with both horizontal and vertical stripes is a grid. Due to the image scaling algorithm, the grid is more visible when the image is zoomed out. [0003] For images containing grid noise, there are currently three ways to deal with them. [0004] 1. Improve the image quality of the camera and improve the optical sensor. This method is expensive and not easy to implement. [0005] 2. The image is smoothed, and the fixed difference between pixels is eliminated by means o...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00G06T7/13
CPCG06T7/13G06T2207/20032G06T5/73G06T5/70
Inventor 高晓阳周中亚杨煦刘强强王玉成宋伟铭李润锋刘敏
Owner BEIJING DAHENG IMAGE VISION
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