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Resolution enhancement by nearest neighbor classified filtering

An image resolution, the closest technology, applied in the field of image processing, can solve problems such as limiting performance

Inactive Publication Date: 2004-04-07
SONY ELECTRONICS INC
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Problems solved by technology

[0003] A second limitation of the binary threshold classification technique is that it is very sensitive to errors and changes in individual pixels
While doing so provides a smooth classification transition, it limits performance

Method used

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  • Resolution enhancement by nearest neighbor classified filtering
  • Resolution enhancement by nearest neighbor classified filtering
  • Resolution enhancement by nearest neighbor classified filtering

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Embodiment Construction

[0011] A method and device for determining the nearest neighbor classification for an input image vector from multiple spatial classifications to improve image resolution are given below. In one embodiment, the nearest neighbor class is determined by first receiving an input image vector to be classified into one of several spatial classes. Each spatial class has a corresponding normalized mean class vector. Normalizes the input image vector. Then determine the weighted distance from the normalized image vector to each normalized mean class vector. The class vectors belonging to the nearest neighboring class to the input image vector are determined on the basis of the weighted distance. Applies a filter corresponding to the nearest neighbor class to an input image vector, increasing image resolution.

[0012] In signal processing, spatial filtering has many applications. For example, given the set of pixels represented by the circles in Figure 1, sample values ​​can be est...

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Abstract

A method and apparatus for enhancing image resolution by determining a nearest neighbor class for an input image vector from a plurality of spatial classes are disclosed. In one embodiment, the nearest neighbor class is determined by first receiving the input image vector that is to be classified into one of several spatial classes. Each spatial class has a corresponding normalized mean class vector. The input image vector is normalized. Then, the weighted distances from the normalized image vector to each normalized mean class vector are determined. The class vector which is the nearest neighbor class to the input image vector is determined based on the weighted distances. A filter corresponding to the nearest neighbor class is applied to the input image vector to enhance the resolution of the image.

Description

technical field [0001] The invention relates to the field of image processing. technical background [0002] It has been shown that utilizing spatial classification can improve spatial filtering results. One technique is to gate each pixel in the classification tap to form a corresponding binary value. This binary value is then used to select a spatial classification. But this technique is not proportional to the size of the classification number, because the number of spatial classifications grows exponentially with the number of classification taps. For example, a diamond-tap classifier with a radius of 1 has 5 taps, providing 2 5 = 32 spatial categories. A diamond-tap sorter with a radius of 2 has 13 taps, providing 2 13 = 8192 spatial categories. More taps require millions of categories. [0003] A second limitation of the binary threshold classification technique is that it is very sensitive to errors and changes in individual pixels. This sensitivity introduces...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T3/40G06T5/20G06V10/764H04N7/01
CPCG06T5/20G06K9/6272G06T3/4007G06V10/764G06T5/00G06F18/24137
Inventor T·孔多J·J·卡里Y·弗吉莫里W·K·凯里
Owner SONY ELECTRONICS INC
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