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Image coding method and system based on dictionary learning

An image coding and dictionary learning technology, applied in the field of multimedia information processing and communication, can solve the problems of large training accuracy and reconstruction error, high computational complexity, training and processing, etc.

Inactive Publication Date: 2014-01-01
TSINGHUA UNIV +1
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Problems solved by technology

Existing dictionary learning methods have high computational complexity and large algorithm cache space overhead, which cannot be used for training and processing large-scale image samples. Although existing online learning algorithms provide the possibility to deal with a large number of samples, the training accuracy Larger error with reconstruction

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  • Image coding method and system based on dictionary learning
  • Image coding method and system based on dictionary learning
  • Image coding method and system based on dictionary learning

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Embodiment Construction

[0070] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0071] Such as figure 1 As shown, the present invention provides a kind of image coding method based on dictionary learning, comprises the following steps:

[0072] Step A: sample training, randomly select image blocks from a large number of image samples, perform dictionary learning based on batch processing sparse representation (BSR), and obtain a dictionary matrix;

[0073] In this step, the following steps are further included:

[0074] A1. Randomly select image blocks from image samples, and initialize the intermediate variable matrix H 0 ←0,G 0 ←0, where H 0 It is a real number matrix with m rows and m columns, m is the number of columns of the dictionary matri...

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Abstract

The invention discloses an image coding method and system based on dictionary learning. The method comprises the steps that image blocks are randomly selected from an image sample to carry out sparse representation based on batch processing, and a dictionary matrix is solved through an alternative optimization method; according to the obtained dictionary matrix, the sparse representation processed in batch is utilized to carry out sparse representation on the image blocks to be coded, and quantification entropy coding is carried out on nonzero coefficients in sparse coefficient vectors; decoding and sparse reconstruction are carried out on the coded image at a decoding end according to the obtained dictionary matrix. The system comprises a dictionary learning module of sparse representation based on batch processing, an image coding module and an image decoding module. According to the method and system, the problem that the training sample in dictionary learning is large in scale is resolved, meanwhile reconstruction errors of the image sample are reduced, and rate-distortion performance of image compression is significantly promoted.

Description

technical field [0001] The invention relates to the technical field of multimedia information processing and communication, in particular to an image coding method and system based on dictionary learning. Background technique [0002] In recent years, the number of mobile Internet users has grown rapidly, and people expect to obtain higher-quality multimedia services. Therefore, in an environment where the wireless network bandwidth is still relatively limited, how to provide high-quality multimedia services and meet the ever-increasing user experience requirements is facing a huge challenge. For example: mobile multimedia applications such as browsing and sharing of a large number of high-quality pictures and photos on mobile terminals. [0003] In order to solve the contradiction between high-quality user experience requirements and limited bandwidth, high-quality image coding and compression technology is necessary. Among them, signal transformation and representation m...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T9/00G06K9/66
Inventor 陶晓明孙逸鹏葛宁陆建华
Owner TSINGHUA UNIV
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