Image Set Compression with Content Adaptive Sparse Dictionary

doi:10.3969/j.issn.1006-2475.2017.11.012

Abstract

Abstract: In the big data era, there is a huge amount of image information, which brings considerable difficulties to the actual storage, transmission, etc. The main purpose of image set compression is to make use of its own content and remove redundant information of images. In this paper, an image set compression scheme based on content adaptive sparse dictionary is proposed. A set of classification sparse dictionaries is learned by using image content classification information, and these dictionaries will be used to replace the traditional transform. In addition, this paper uses the nonlocal similarity of image patches to optimize the problem in decoder. Experimental results demonstrate that the proposed method for image set compression outperforms JPEG method and the compression scheme based on recursive least squares dictionary learning algorithm (RLS-DLA) in terms of compression property.

Key words: sparse representation, image set compression, dictionary learning, content adaptive, image coding

CLC Number:

TP391

LI Qiang. Image Set Compression with Content Adaptive Sparse Dictionary[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2017.11.012.

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