Image interpolation method and device based on spline surface

Abstract

The invention discloses an image interpolation method and an image interpolation device based on a spline surface. The image interpolation method comprises the following steps that: a control point matrix containing pixels to be interpolated in an original image is selected; and the pixel value of each pixel of an interpolation matrix containing the pixels to be interpolated in an enlarged image through a spline surface function and the control point matrix. With the adoption of the image interpolation method based on the spline surface and the device, the spline surface function can be adopted to construct a curved surface so as to realize the interpolation of the image, serration generated by the conventional interpolation method can be well avoided, the values of reference points in the image enlarging process are moderately adjusted, so that the contrast ratio and the effect of the edge of the enlarged image are better improved, and the efficiency of image enlargement reconstruction is ensured through simplification of the algorithm.

Description

technical field [0001] The invention relates to image processing technology, in particular to an image interpolation method and device based on a spline surface. Background technique [0002] Among the traditional image interpolation algorithms, nearest neighbor interpolation is relatively simple and easy to implement, and it was widely used in the early days. However, this method produces noticeable jagged edges and mosaics in new images. The bilinear interpolation method has a smooth function, which can effectively overcome the shortcomings of the nearest neighbor method, but it will degrade the high frequency part of the image and make the image details blurred. When the magnification is relatively high, high-order interpolation, such as bicubic and cubic spline interpolation, is better than low-order interpolation. These interpolation algorithms can make the pixel gray value generated by interpolation continue the continuity of the original image gray level change, so ...

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Problems solved by technology

(2) The method based on the edge of the high-resolution image after interpolation This kind of interpolation method: first use the traditional method to interpolate the low-resolution image, then detect the edge of the high-resolution image, and finally perform special processing on the edge and nearby pixels to remove blur , to enhance the edge of the image. This scaling algorithm can achieve better processing results in terms of edges and details. To obtain high-precision processing results, it can only sacrifice speed and adopt a more complex algorithm.

[0004] Considering the above analysis comprehensively, when using image interpolation algorithm for image scaling, there are always two contradictory factors, image processing accuracy and image reconstruction speed, which are difficult to balance

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