Image picture noise reduction method used for starlight-class camera

Abstract

The invention discloses an image picture noise reduction method used for a starlight-class camera. The image picture noise reduction method comprises the following steps: firstly selecting a filtering window of 3*3 pixel points, and setting window weight and an initial value of the filtering window; reading gray value of each corresponding pixel point under the filtering window; carrying out comparison sorting on the read gray values, and recording maximum, minimum and an intermediate value of pixel gray values in the current filtering window; setting weight of each pixel point; enabling W to be the sum of weights of all the windows, Sum to be an accumulated value of products of all the pixel gray values in the filtering window and the weights, and value of Sum / W to be replaced by the pixel gray value at the center of the window; and completing weighted mean filtering according to the replaced pixel gray value at the center of the window. The image picture noise reduction method has the advantages that Gaussian noise in an image under large gain is eliminated, effect of inhibiting impulse noise of hardware and temperature amplification is also better, and edge detail of the image is better reserved.

Description

technical field [0001] The invention relates to the application field of computer software, in particular to an image frame noise reduction method for a star-level camera. Background technique [0002] When the camera is in a dark scene at night, as the gain increases, the picture noise will become larger, and the existing camera noise reduction technology generally uses mean filtering, and the main method is to select a window template, generally 3×3 or 5×5, scan the window horizontally and vertically along the image data, read the corresponding pixel gray value under the window, and take the average value of these pixels to replace the pixel gray value in the center of the window. The common mean filter has a better effect on Gaussian noise filtering, but it cannot filter out some impulse noise well. [0003] Generally, when the illumination of a starlight camera is small, the gain will be large, and it is easy to amplify some interference noise, such as white noise. At t...

AI Technical Summary

Problems solved by technology

The common mean filter has a better effect on Gaussian noise filtering, but it cannot filter out some impulse noise well

[0003] Generally, when the illumination of a starlight camera is small, the gain will be large, and it is easy to amplify some interference noise, such as white noise. At this time, Gaussian noise and impulse noise coexist at the same time, and the simple mean filter cannot achieve a good filtering effect.