Fuzzy detection method for SVD (Singular Value Decomposition) on the basis of image DCT (Discrete Cosine Transform) domain

Abstract

The invention puts forward a fuzzy detection method for SVD (Singular Value Decomposition) on the basis of an image DCT (Discrete Cosine Transform) domain. The method comprises the following steps that: firstly, calculating the gradient map of an image to be detected, wherein the edge information of the image can be obtained from the gradient map; then, carrying out partitioning on the gradient map, and carrying out DCT, wherein the alternating current coefficient of the DCT domain reflects the edge and the definition of the image; then, analyzing the alternating current coefficient information of the DCT domain by a difference matrix, calculating the singular value of the difference matrix, and constructing a response function to express the fuzzy degree of the image of a block; and finally, using a mean value and a variance to carry out normalization on an image block response sum to eliminate the influence of image contents. An experiment indicates that the fuzzy score obtained by the method is highly consistent with the subjective evaluation score of a human eye for the image. The detection model disclosed by the invention considers the characteristics that the edge becomes wide, the definition becomes weak and the like in an image blurring process, the influence of image contents is effectively eliminated, so that detection accuracy is high, in addition, detection efficiency is high, and integral performance is superior to the integral performance of a previous method.

Description

technical field [0001] The invention relates to the field of image blur detection, and proposes a blur detection method based on SVD decomposition in the DCT domain of images, which can quickly and accurately detect blur images. Background technique [0002] As one of the carriers of information transmission, digital images play an important role in daily life or work. For example, the popularity of mobile phones has made mobile phone photography one of people's daily entertainment items; satellite remote sensing images have brought convenience to agriculture, industry and the environment, etc. However, some distortions will inevitably be introduced in the process of acquisition, compression, transmission and storage of digital images, which not only affects the visual experience, but may also cause huge losses. Image blurring is the most common type of distortion, so the detection of image blurring has attracted more and more attention. [0003] Although the human eye has...

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Problems solved by technology

[0003] Although the human eye has the ability to distinguish blurred images from clear images, it has disadvantages such as time-consuming and heavy workload. Therefore, it is particularly important to use computers to detect blurred images.

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