An image filtering method, storage medium and terminal equipment
An image filtering and input image technology, applied in the field of image processing, can solve the problems of algorithm halo, high computational complexity, and depicting image content, etc.
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Embodiment 1
[0064] This embodiment provides an image filtering method, such as figure 1 As shown, the method includes:
[0065] S10. For a target pixel in the input image, acquire at least one sub-window of the target pixel, wherein the target pixel is located on a sideline of the sub-window.
[0066] Specifically, the input image is an image to be processed, which may be an image captured by a camera, or an image sent by an external terminal. Each target pixel point in the input image refers to each pixel point included in the input image. It is assumed here that the number of pixels of the input image is M*N, that is, the number of rows of the pixel matrix of the input image is M, and the number of columns is N. For the target pixel in the input image, its position in the pixel matrix of M*N is used as the coordinate position of the target pixel, and is recorded as (i, j), where i is the target pixel in The row number of the input image pixel matrix, j is the column number of the tar...
Embodiment 2
[0135] In the input image, there are few borders with an angle of 45 degrees, and when there are only horizontal or vertical borders, four sub-windows, left sub-window, right sub-window, upper sub-window and lower sub-window, can be obtained through the description of Embodiment 1, and the output The formula for calculating the pixel value is as follows:
[0136]
[0137]
Embodiment 3
[0139] On the basis of Embodiment 2, each sub-window also contains three scales, respectively (r, r+2, r-2), correspondingly, each sub-window will calculate three scales (r, r+2, r -2) Valuation. Here, taking the left sub-window as an example, the target pixel estimates of the three scales are expressed as:
[0140]
[0141] Then for 4 sub-windows, 3 scales for each sub-window, a total of 12 estimates are obtained. Finally, the value of the corresponding pixel of the output image is taken as the value of the corresponding pixel of the output image among the 12 evaluations with the smallest distance from the target pixel of the input image.
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