A High Definition Image Classification Method Based on Dictionary Learning

Abstract

The invention discloses a high-definition image classification method based on dictionary learning and relates to the field of digital image processing. The high-definition image classification method based on the dictionary learning comprises the following steps of extracting visual characteristics of all high-definition image samples, for the visual characteristics, conducting sparse coding on the high-definition image samples, continuously conducting dictionary learning through the iterative method until classification errors are less than a threshold, determining a classification dictionary of high-definition image classes, determining a corresponding weight based on the degree of influence of each visual characteristic on one reconstruction error, establishing an image nonlinear classifier based on the dictionary of the high-definition image classes and the corresponding weights of the visual characteristics, and determining the class of the high-definition image. Through the high-definition image classification method based on the dictionary learning, the dictionary learning through the sparse coding can be conducted, and sparse codes with a high distinction degree can be obtained. Therefore, the high-definition image classification method based on the dictionary learning has good self adaptability, to sample space distribution of a high-definition image data set, has better robustness for a complicated image, and has good generality and high practical value.

Description

technical field [0001] The invention relates to the field of digital image processing, in particular to a high-definition image classification method based on dictionary learning. Background technique [0002] At present, with the rapid development of computer networks, the development and wide application of digital media technology and intelligent information processing technology, large-scale image resources continue to emerge. In the face of massive image information, how to classify or label images in order to quickly and effectively retrieve the images of interest from the massive image data has become a research hotspot in artificial intelligence and pattern recognition. It has a wide range of applications in industrial production, aerospace, biomedicine, traffic monitoring and other fields. [0003] During the decades of research on image classification, various classification methods based on different theories have emerged. However, a unified theoretical system ha...

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Problems solved by technology

[0011] The purpose of the present invention is to provide a classification method for high-definition images, which can solve the problems of the current supervised classification method, such as slow classification speed, exponential growth of complexity as the number of features increases, and low correlation features affecting classification accuracy.

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