Large scale enlarging method with high performance for digital image based on subspace decomposition

A subspace decomposition, digital image technology, applied in image enhancement, image data processing, complex mathematical operations, etc.

Inactive Publication Date: 2003-05-07
TSINGHUA UNIV
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  • Abstract
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Problems solved by technology

However, even if the nearest neighbor interpolation method is used, the amount of calculation is sti

Method used

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  • Large scale enlarging method with high performance for digital image based on subspace decomposition
  • Large scale enlarging method with high performance for digital image based on subspace decomposition
  • Large scale enlarging method with high performance for digital image based on subspace decomposition

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Experimental program
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specific Embodiment approach

[0069] (1) determine block size, carry out block to digital image;

[0070] (2) According to the adopted one-dimensional interpolation operator, determine whether to perform bordering on the block operator: the number of columns to be bordered on the left and right sides of each sub-graph is: o=p / 2-1, p is one-dimensional interpolation The length of the operator, which is an even number. For example, the length of the nearest neighbor interpolation and linear interpolation operators is 2, so no fringing is required, and the length of the cubic interpolation operator is 4, and one column of fringing is required. Set the size of the sub-picture block after bordering as M*L ', L'=L when not bordering; Just enter the next step directly when not needing bordering;

[0071] (3) Fast SVD is performed on each sub-graph, that is, only L' singular values ​​and 2L' singular vectors are calculated;

[0072] (4) Perform one-dimensional interpolation on 2L' singular vectors. Any existing...

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Abstract

High efficient digit image large size amplification method based on subspace dissolution characterizes in converting two-dimension image interpolation into several singular vectors one-dimension interpolation containing singular value dissolution, singular value vector one-dimension interpolation and singular value restructure successively and greatly reducing the interpolation complexity by split, the ratio is reduced along with the increase of amplification of the operation time of this invented method and that of the image two-dimension three-interpolation method in a same image dimension and split dimension, such as a split dimesnion is 16*8, amplified dimension is 120 inch, if image three times interpolation is 1, image linear interpolation time is 0.42, image latest interpolation time is 0.295.

Description

technical field [0001] The invention relates to a high-efficiency digital image large-scale enlargement method based on subspace decomposition, which belongs to the technical field of digital image processing. Background technique [0002] Image nearest neighbor interpolation, linear interpolation, and cubic interpolation methods are the most commonly used image enlargement techniques in digital image processing, but they all have a large amount of computation. Also relatively fast nearest neighbor interpolation and linear interpolation methods perform poorly on interpolation. In general, one needs to use cubic interpolation if good interpolation results are desired. If fast interpolation is required, the only option is to sacrifice the interpolation effect and choose the nearest neighbor interpolation. However, even if the nearest neighbor interpolation method is used, the amount of calculation is still too large when performing large-scale image enlargement, which cannot...

Claims

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Application Information

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IPC IPC(8): G06F17/16G06T5/00
Inventor 陆文凯
Owner TSINGHUA UNIV
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