Remote sensing image quality definition comprehensive evaluation module and evaluation method

Abstract

The invention relates to a remote sensing image quality evaluation module and a selection method. The definition of a remote sensing image is calculated by adopting multiple functions; normalization processing is performed on the definition of the images calculated by the multiple functions; the maximum value and the minimum value in the normalized definition values are eliminated, and corresponding scores are averaged and output; and for a plurality of images of the same target, an image with a score exceeding a set threshold is selected as an effective image to be output. According to the invention, the definition of different images is evaluated by comparing definition values of different images, the definition of a single image can be evaluated according to the definition value of thesingle image, the definition of the images can be accurately distinguished, and the quality of remote sensing load output images is ensured. The method can achieve the quick and automatic evaluation of different evaluation indexes of the image, enables the processing time of one image to be less than one minute, does not need manual intervention, and is suitable for the quick and automatic processing of a large number of images.

Description

technical field [0001] The invention relates to the technical field of remote sensing image processing, in particular to a remote sensing image quality definition comprehensive evaluation module and an evaluation method. Background technique [0002] With the rapid development of digital remote sensing imaging technology, the requirements for image quality in various application fields are also increasing, and image clarity has gradually become an important indicator for judging image quality. However, the current objective evaluation method of image clarity is not mature enough. It is of great significance to carry out the research on the general objective evaluation method of image clarity and realize the rapid evaluation of large-scale digital images for the processing and application of remote sensing images. [0003] Image sharpness evaluation methods are divided into subjective evaluation methods and objective evaluation methods. In the subjective evaluation method, o...

AI Technical Summary

Problems solved by technology

However, there is a lack of absolute evaluation of image clarity, and it is impossible to determine the quality of an image based on the evaluation results of the clarity of an image.

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