An image resampling method and system

Abstract

The invention provides an image resampling method relevant with content and an image resampling system relevant with the content and relates to the technical field of computer image processing. An existing resampling method is usually relevant with a position of a sampling point and lacks of consideration about content of a sampling portion so that a result image has quality deteriorating problems such as mosaics on the image and image vagueness. With the image sampling method, a basic sampling value is obtained with a regular interpolation algorithm, according to adjacent content of a to-be-sampled portion of an original image, the basic sampling value undergoes weighted correction and a final sampling result is synthetised. The problem of vague images in the existing method and the system is avoided with the image resampling method and the image resampling system, and at the same time, high fidelity can be ensured. The image resampling method and the image resampling system can be suitable for application such as image rotation, displacement, abstraction and the like.

Description

technical field [0001] The invention relates to the technical field of computer image processing, in particular to a high-quality image resampling method and system. Background technique [0002] Resampling is a basic task of image processing, and image resampling is required for processing such as image rotation, translation, and scaling. In the prior art, commonly used resampling methods include nearest neighbor method, bilinear interpolation method, bicubic interpolation method and the like. [0003] Among the above-mentioned existing methods, the nearest neighbor method is the fastest, but the mosaic is serious, and the sampling results are discontinuous; the bilinear interpolation method has a continuous result, but the image becomes blurred, as if it has been smoothed; the bicubic interpolation method, or It is called the cubic convolution interpolation method, which was first seen in "Cubic convolution interpolation for digital image processing" (1981), and is the mo...

AI Technical Summary

Problems solved by technology

Although the fuzziness of the sampling results of the bicubic interpolation method is lighter than that of the bilinear interpolation method, it still cannot avoid the fuzziness.

[0004] In addition, some edge correction-based resampling research literatures try to solve the blurring problem, but introduce other distortion problems, which are not of generalization value

[0005] The existing resampling methods are usually only related to the position of the sampling point, and lack of consideration of the content of the sampling part, which leads to the quality degradation of the resulting image such as mosaic or blur

Among many resampling methods, the bicubic interpolation method is widely used because of its fast calculation and high fidelity, but it is easy to cause blurring of the edge, especially when the image is enlarged

Images