Image restoration method and system and storage module

Abstract

An image restoration method and system, and a storage module, the image restoration method comprising: obtaining an original image and shooting information of the original image, the shooting information comprising a shooting location and a shooting angle; the shooting positioning is positioning when the camera device shoots the original image, and the shooting angle comprises a wide angle and a pitch angle when the camera device shoots the original image; the method comprises the following steps: acquiring symbolic features of calibrated geographic coordinates from an original image, acquiring pixel points corresponding to the symbolic features and marking the pixel points as feature pixel points, and marking the geographic coordinates corresponding to the symbolic features as reference coordinates; and combining shooting positioning and reference coordinates to calculate the depth of field of the feature pixel points as a reference depth of field. According to the method and device, it is guaranteed that the depth of field of the feature pixel points is obtained quickly, conveniently, efficiently and accurately, a foundation is laid for accurate calculation of the depth of field of the remaining pixel points on the original image subsequently, and therefore guarantee is provided for high-quality restoration of the original image.

Description

technical field [0001] The invention relates to the field of image processing, in particular to an image restoration method, system and storage module. Background technique [0002] As image processing technology is widely used in various industries, people's pursuit of image quality is getting higher and higher. In this case, technical research on image restoration emerges in an endless stream. [0003] The existing and most recommended image restoration technology is to restore the original image by combining the pixel depth of field and the pre-built image restoration model. At present, the depth of field of pixels can be obtained according to two methods: one is to manually measure the distance from the shooting position to some pixels on the original image, that is, the depth of field; the other is to estimate the distance from the shooting position to some pixels on the original image Distance is depth of field. Of the above two methods, the former is difficult to m...

AI Technical Summary

Problems solved by technology

Of the above two methods, the former is difficult to measure, takes a long time, and is not easy to implement; the latter has large errors and it is difficult to guarantee the quality of image restoration

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