Image interpolation method and system based on prediction gradient
A technology of interpolation method and prediction method, which is applied in the direction of graphics and image conversion, image data processing, instruments, etc., and can solve problems such as differences, poor picture quality, and long time consumption
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Embodiment 1
[0096] The image interpolation method based on the prediction gradient in this embodiment includes:
[0097] Determine whether the pixel to be interpolated is an edge pixel,
[0098] If the pixel to be interpolated is a non-edge pixel, a linear interpolation method is used for interpolation to obtain a high-resolution image;
[0099] If the pixel to be interpolated is an edge pixel, a non-linear interpolation method is used for interpolation to obtain a high-resolution image.
[0100] In this embodiment, given a continuous tone gradient image I(i, j), the gradient image can be regarded as a two-dimensional function about (i, j). In order to judge whether a certain pixel is an edge pixel, the present invention needs to calculate the gradient value of this pixel, and the calculation formula is as shown in formula (1):
[0101] Formula 1)
[0102] here, Refers to the gradient value on the pixel (i, j), is the directional derivative of the LR image, θ represents the dire...
Embodiment 2
[0106] In this embodiment, the image interpolation method based on the prediction gradient, on the basis of Embodiment 1, the nonlinear interpolation method specifically includes the following contents.
[0107] The greater the edge contrast, the easier it is to be observed by the human eye. The reason why the human visual system can observe the edge of a natural gradient image is because of the large gradient difference between adjacent regions, such as Figure 4 As shown in (a), the difference between such gradients can be referred to as contrast or edge intensity in the present invention. Using an edge detection algorithm, for Figure 4 (a) Given an image, one will get Figure 4 In the edge result graph shown in (b), the edge line formed at this time is the real edge of the gradient image, and it is also the edge observed by the human eye. But it is worth noting that the greater the edge strength, the easier it is to be regarded as an edge by the human eye. Unfortunately...
Embodiment 3
[0127] The image interpolation system based on the prediction gradient in this embodiment includes:
[0128] The edge pixel judging module is used to judge whether the pixel to be interpolated is an edge pixel,
[0129] If the pixel to be interpolated is a non-edge pixel, the linear interpolation module uses a linear interpolation method to perform interpolation to obtain a high-resolution image;
[0130] If the pixel to be interpolated is an edge pixel, the nonlinear interpolation module performs interpolation using a nonlinear interpolation method to obtain a high-resolution image.
[0131] In this embodiment, the performance of the same color image in different color spaces is different. Among them, the RGB color space is the most important and the most widely used color space, and the other color spaces are linear or nonlinear changes of the RGB color space. In the color space represented by RGB, a color picture can be expressed as the following model:
[0132]
[01...
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