Image classification method based on learning of FISHER multi-level dictionary

Abstract

The invention discloses an image classification method based on learning of a FISHER multi-level dictionary. The method includes the steps of constructing an image classification system, importing sample images, and utilizing a sparse representation matrix of an over-complete dictionary to conduct primary appropriate classification on each sample image; conducting learning at different levels on the images classified by the over-complete dictionary on the basis of the FISHER multi-level dictionary, and obtaining specific information and common information of each class of images; using a discriminant of a FISHER criterion principle to reinforce the distinguishing capacity of the dictionary at different levels to form an optimal image classification discrimination standard. The image classification method based on learning of the FISHER multi-level dictionary can better catch various images which have most distinctive features under comparison with other images, each image has the mostunique features, and the distinguishing efficiency and accuracy are improved.

Description

technical field [0001] The present invention relates to the technical field of image processing, relates to an image classification method, in particular to an image classification method based on FISHER multi-level dictionary learning. Background technique [0002] Sparse coding has become a hot topic in the field of computer vision and pattern recognition, and has been widely used to deal with various problems, such as image super-resolution, image denoising, image retrieval, image classification, object detection, and event detection. The core idea of ​​sparse coding is to encode each image feature vector as a linear combination of several atoms from an over-complete dictionary, and various applications of sparse coding show the importance of discriminative features in dealing with different problems. [0003] In the past decade, many techniques have been developed to improve the performance of sparse coding and dictionary learning, resulting in many state-of-the-art resu...

AI Technical Summary

Problems solved by technology

[0004] The main purpose of the present invention is to solve the problem that the accuracy of image classification in the prior art is not high enough, and to provide an image classification method based on FISHER multi-level dictionary learning. The specific technical scheme is as follows:

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