PCNN model-based compression encoding and decoding methods of still image and systems thereof

A still image and encoding system technology, applied in the field of image processing, can solve problems such as large amount of computation and failure to meet real-time requirements, achieve a large compression ratio, and eliminate adverse effects

Inactive Publication Date: 2012-04-11
LANZHOU UNIVERSITY
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Problems solved by technology

[0014] However, the Schmidt orthogonalization method that is most used at present has a very large amount of calculation, which is far from meeting the real-time requirements. This requires the use of other schemes or optimization of the Schmidt orthogonalization scheme or finding its fast algorithm

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  • PCNN model-based compression encoding and decoding methods of still image and systems thereof
  • PCNN model-based compression encoding and decoding methods of still image and systems thereof
  • PCNN model-based compression encoding and decoding methods of still image and systems thereof

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Embodiment Construction

[0020] Such as figure 1 Shown, the present invention is based on the still image compression codec method and system of the pulse-coupled neural network model, in the encoding system, the first subsystem adopts the pulse-coupled neural network model to carry out image segmentation to the still image; the second subsystem Encoding the segmentation results, including the encoding of the segmentation block and the encoding of the specific grayscale in the segmentation block; wherein, the encoding of the segmentation block adopts chain code encoding, and the specific grayscale encoding adopts the Schmidt orthogonalization scheme, and the corresponding orthogonal The cross-base coefficients are encoded; in the decoding system, the original image is restored according to the encoded data of the segmented block and the coded data of the gray level of the segmented block.

[0021] A still image compression coding method and system based on the PCNN model, wherein a grayscale still ima...

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Abstract

The invention relates to a pulse coupled neutral networks (PCNN) model-based compression encoding and decoding methods of a still image and systems thereof. More particularly, the invention relates to a high-efficient segmentation compression encoding method of a still image and a system thereof as well as a corresponded decoding method and a system thereof. According to the encoding system, a first subsystem employs a PCNN model to carry out image segmentation on a still image; a second subsystem carries out encoding on the segmentation result, wherein the encoding process comprises encoding of segmentation blocks and encoding of concrete gray scales in the segmentation blocks; besides, the segmentation block encoding employs chain code encoding and the concrete gray scale encoding employs a Schmidt orthogonalization scheme; and encoding is carried out on corresponded orthogonal basis coefficients. According to the decoding system, an original image is recovered according to decoded segmentation block data and encoded data of the segmentation block gray scales.

Description

technical field [0001] The invention belongs to the field of image processing. In particular, it relates to a method and system for compression coding of still images using PCNN and a method and system for compression coding of large resolution images. Background technique [0002] In the second-generation coding technology, two directions are mainly used, one is to divide the image into different frequency bands, and then encode the different frequency bands; the other is to divide the image into blocks, and then encode each block. [0003] So far, image compression methods based on block operations have been widely used due to their advantages of fast calculation speed and no need for image shape information, such as still image compression standard JPEG, and video compression standards such as H.261, MPEG, etc. However, this type of compression algorithm also has its own inherent defects, such as gray discontinuity (block effect) at the boundary of each block, which will...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T9/00
Inventor 马义德余文锐赵荣昌齐春亮史飞苏茂俊
Owner LANZHOU UNIVERSITY
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