Image processing device and method, data processing device and method, program, and recording medium

An image processing device and image technology, applied in image data processing, image data processing, image communication and other directions, can solve problems such as image quality deterioration

Inactive Publication Date: 2014-07-30
FUJIFILM CORP
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, there is a problem that when an image that does not satisfy the condition is input, the quality of the image restored after projection deteriorates

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Image processing device and method, data processing device and method, program, and recording medium
  • Image processing device and method, data processing device and method, program, and recording medium
  • Image processing device and method, data processing device and method, program, and recording medium

Examples

Experimental program
Comparison scheme
Effect test

example 2

[0384] Although in Image 6 with 12 11 illustrates a configuration in which the learning step and the restoring step are performed by one image processing device, but the image processing device performing the learning step and the image processing device performing the restoring step may be arranged separately. In this case, it is desired that the image processing apparatus that manages the restoration step can externally acquire the information of the individually created projection relationship (intrinsic projection matrix and projection tensor). A media interface or a communication interface corresponding to an optical disc or other removable storage media can be used as the information acquisition component.

example 3

[0386] Although LPP is illustrated in the embodiment as a projection using local relations, various learning methods such as Local Linear Embedding (LLE), Local Tangent Space Arrangement (LTSA), Isomap, Lapp Lass Feature Maps (LE) and Neighborhood Preserving Embeddings (NPE).

example 4

[0388] exist Image 6 In the embodiment described in , the modality of the tile and the resolution of the four modalities described in Table 1 are treated as known elements for setting the conditions to simplify the description, and by focusing on the "pixel value ” and “individual differences” through the projective route of the pixel-intrinsic space and the individual-difference intrinsic space from the pixel-real space. However, the design of projected routes is not limited to performing this example in the present invention. Various eigenspaces can be selected as eigenspaces in the projected route that vary according to the modality.

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

Generate an intrinsic projection matrix (#14) from a learning image population (#10) comprising high-quality images and low-quality image pairs by using projection computation (#12) of local relations to create a projection core tensor (#16), which Projection kernel tensors are used to define the correspondence between low-quality images and intermediate eigenspaces and the correspondence between high-quality images and intermediate eigenspaces. Create (#24) the first sub-kernel tensor from the projection kernel tensor based on the first setting, and project (#30) the input low-quality image (#20) based on the intrinsic projection matrix and the first sub-kernel tensor, to compute the coefficient vector in the intermediate eigenspace. The coefficient vector is projected (#34) based on the second sub-kernel tensor created from the projected kernel tensor by the second setting (#26) and based on the intrinsic projection matrix to obtain a high-quality image (#36). This can realize highly accurate and highly robust (robust) image conversion, which can ease the input condition of an image as a conversion source, and can reduce processing load, can speed up processing, and can suppress required memory size.

Description

technical field [0001] The present invention relates to an image processing device and method, a data processing device and method, a program, and a recording medium, and in particular, to an image data (low image quality information) suitable for restoring, interpolating, enlarging, and encoding that do not exist in image data (low image quality information) before processing. Image processing technology and data processing technology for high image quality information. Background technique [0002] A technique is proposed as a method to generate a high-resolution output image from a low-resolution input image, in which pairs of low-resolution and high-resolution images of multiple image contents are learned in advance, and the low-resolution information obtained from the A conversion (projection) relationship to high-resolution information, and using the projection relationship to generate (restore) an image including high-resolution information from a low-resolution input...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G06T1/00H04N1/387H04N7/01
CPCH04N19/172H04N19/124H04N19/132H04N19/0026H04N19/23G06T3/4053H04N19/61H04N19/00781G06K9/6247H04N19/00248H04N19/00436G06K9/00275H04N19/46H04N19/00545H04N19/0009H04N19/33H04N19/00266H04N19/00127H04N19/17H04N19/167H04N19/004G06V40/169G06V10/7715G06F18/2135
Inventor 龟山祐和
Owner FUJIFILM CORP
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap