Non-reference image quality evaluation method based on high-quality natural image statistical magnitude model

A technology of natural images and reference images, which is applied in the fields of image processing, image communication, image detection, image storage, and image compression, and can solve problems such as inaccurate evaluation results and weak generalization ability

Active Publication Date: 2014-08-20
TONGJI UNIV
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Problems solved by technology

[0009] The purpose of the present invention is to provide a no-reference image quality evaluation method based on a high-quality natural image statistical learning model, which solves the shortcomings of the traditional no-reference image quality evaluation method, such as weak generalization ability and inaccurate evaluation results, and satisfies practical applications. Requirements for no-reference image quality assessment methods

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  • Non-reference image quality evaluation method based on high-quality natural image statistical magnitude model

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[0091] The non-reference image quality evaluation method based on the high-quality natural image statistical learning model shown in the present invention: first learn the parameters corresponding to the multivariate Gaussian model from high-quality natural image blocks; for the test image, first divide it into equal sizes image blocks, and extract the multivariate Gaussian model of each image block; use the Bhattacharyian distance to determine the distance between the multivariate Gaussian models, thereby determining the quality of the distorted image quality block; use visual saliency to linearly weight the quality of all distorted image blocks, Finally, the objective evaluation score of the test image is obtained.

[0092] figure 1The flow chart of the non-reference image quality evaluation method shown in the present invention is provided, and the details of each step are described in detail below:

[0093] (1): Learning a multivariate Gaussian model (μ, Σ) as a benchmark...

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Abstract

The invention discloses a non-reference image quality evaluation method based on a high-quality natural image statistical magnitude model. The method includes the steps that firstly, parameters corresponding to a multi-element Gaussian model are learnt from first image blocks of a high-quality natural image; a test image is divided into second image blocks which are the same in size, and a multi-element Gaussian model of each second image block is extracted; the distances between the multi-element Gaussian models are determined through a bhattacharyya distance, and then the quality of distorted image quality blocks is determined; the quality of all the distorted image blocks are linearly weighted through visual saliency, finally the objective evaluation grade of the test image is acquired, the problem that an existing evaluation method is low in generalization ability can be well solved, and the requirements of actual application for the non-reference image quality evaluation method are met.

Description

technical field [0001] The invention belongs to the technical field of image processing, relates to image quality evaluation, and can be widely used in the fields of image compression, image storage, image communication, image detection and the like. Background technique [0002] An image is a similar and vivid description or portrait of an objective object, and is the most commonly used information carrier in human social activities. Along with the development of signal processing and computer science and technology, image engineering has also become a subject with rich content and rapid development. An image system includes image acquisition, display, storage, communication, processing and analysis. It is widely used in various fields of the national economy, such as: scientific research, industrial production, medical and health care, education, entertainment, management and communication, etc. It plays an important role in promoting social development and improving peop...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/46
Inventor 张林顾中一李宏宇沈莹
Owner TONGJI UNIV
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