Image and video amplification method and relevant image processing device

Abstract

The invention relates to an image and video amplification method and a relevant image processing device. The method comprises a preprocessing module and a composite amplification module, wherein the preprocessing module is used for executing high-pass filtering processing to an input image to extract the high-frequency part of the input image and is used for executing image decomposition processing to the input image to decompose the input image into smooth areas and marginal areas; and the composite amplification module is used for conducting amplification processing to the original input image and the smooth areas through simple interpolation operation and is used for conducting amplification processing to the marginal areas and the high-frequency part through both complex interpolationoperation and simple interpolation operation. By adopting the method, the amplification results of the original input image, the smooth areas, the marginal areas and the high-frequency part can be fused, i.e. an output image with features of saw tooth resistance, clear-cut margin, rich detail, high contrast and the like can be output according to a preset amplification scale under the circumstance that the operation workload is small, the complexity is low and the speed is high.

Description

Image and video magnification method and related image processing device technical field The present invention relates to an image and video upscaling method, in particular to a method for enlarging a low-resolution input image and displaying it on a high-resolution video device, so that the enlarged output image still has anti-aliasing, anti-aliasing, A method characterized by sharp edges, rich details, and strong contrast. Background technique In recent years, various digital camera devices (such as: digital cameras and video cameras, etc.) have been continuously introduced, not only the image quality is getting higher and higher, the product size is getting smaller and smaller, and its market price is also getting cheaper. Therefore, the digital camera devices have become It has become increasingly popular and has become an indispensable and important tool in people's daily life and work. Take the mobile phone with camera function that is quite popular in the market as...

AI Technical Summary

Problems solved by technology

By the way, image processing industry and designers have carried out many years of research on image and video amplification technology, whether it is from the initial linear amplification technology to the later edge-based amplification technology, new theories and application methods are constantly emerging. Among them, the commonly used linear amplification techniques include bilinear interpolation (Bilinear Interpolation), bicubic interpolation (Bicubic Interpolation) and Lanzos method (Lanzcos), and the most representative ones are edge-based amplification techniques. It is NEDI (New Edge-Directed Interpolation). However, there are still many shortcomings in these amplification techniques. The magnification technique of the present invention is to perform interpolation (interpolation) according to the gradient direction (gradient direction) along the edge of the image, although problems such as partial edge jaggedness and blurring can be solved, the described edge-based magnification technique is accurate for the edge direction (edgedirection). There is a large dependence on the property, and it is easy to cause interpolation errors due to inaccurate edge directions, especially in areas with rich details and messy edges in the image, the problem of interpolation errors is particularly obvious and serious; in addition, the In order to maintain the accuracy of the results, the edge-based magnification technology often needs to use huge calculations, which can easily cause the problem of low image processing efficiency.

Finally, since the zoom-in techniques currently used generally use the weighted summation of the neighborhood (neighborhood) primitives (pixels) to perform interpolation calculations, which have the effect of low-pass filtering on the original image, so after the image is zoomed in, it cannot It will avoid the loss of sharpness and detail information (high frequency part) that should be on the original image

In view of this, in order to restore the quality of the original image, the image processing industry often performs some enhancement and restoration processing on the image after the image is enlarged, but the processing produces edge overshoot (overshoot) and ringing effect (ringing effect). ) and other new defects

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