Image processing device and processing method thereof

Abstract

The invention discloses an image processing device and a processing method of the image processing device. The image processing device comprises an image correction module, an object motion detection module and an image mixing module. The image correction module estimates block displacement and universe displacement of an image which is not selected relative to a target image and executes displacement correction to generate a corrected image. The object motion detection module judges whether the difference values between the block displacement and the universe displacement are larger than a threshold value or not and judges whether a pixel difference value between each pixel of the target image and each pixel of the corrected image is larger than a difference preset value or not to generate object motion indexes. The image mixing module conducts arithmetic operation on each pixel of the target image and each pixel of the corrected image according to the object motion indexes to generate an ultra-resolution image. The problem of ghosting easily caused by the mixing of a plurality of images can be solved.

Description

technical field [0001] The present invention relates to an image processing device, in particular to an image processing device and an image processing method for generating super-resolution images. Background technique [0002] Traditionally, image interpolation is a commonly used technique for generating super-resolution images. This single image upscaling method includes polynomial interpolation, edge-directed interpolation, and sample-based superresolution. Analysis technology (exampled-based for super-resolution) and so on. [0003] However, the above-mentioned techniques still have shortcomings that need to be improved. For example, although the polynomial interpolation method is simple and has a fast operation speed, it often results in blurred enlarged images due to the lack of high-frequency information of the image, and also produces block effects. However, edge-wise interpolation or sample-based super-resolution techniques require a huge amount of computation. T...

AI Technical Summary

Problems solved by technology

[0003] However, the above-mentioned technologies still have shortcomings that need to be improved. For example, although the polynomial interpolation method is simple and has a fast calculation speed, it often causes the enlarged image to be blurred due to the lack of high-frequency information of the image, and it will produce block effects.

However, edge-wise interpolation or sample-based super-resolution techniques require a huge amount of computation

Therefore, the image quality is greatly limited by the technology of image enlargement from a single image enlargement

[0004] However, if you want to use the technology of mixing multiple image sequences to generate enlarged images, the most common side effect is ghosting

The cause of the ghosting phenomenon is that when the same scene is continuously shot, individual objects in the scene are moving, and when mixing images, the overall displacement (or camera displacement) of the image is corrected, which does not affect the overall displacement of the scene. Individual objects are corrected, so if there are individual moving objects in the image, it will cause ghosting in the blended image

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