Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Selective image stylizing method based on nonlinear filtering

A non-linear filtering and stylization technology, applied in image data processing, 2D image generation, instruments, etc., can solve the problems of costing a lot of manpower, material and financial resources, and less selective stylization methods, so as to achieve simple and high-efficiency The effect of precision and good operating efficiency

Inactive Publication Date: 2011-04-13
ZHEJIANG UNIV
View PDF1 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] The selective image stylization method based on nonlinear filtering belongs to the field of non-realistic image processing. At present, there are many methods for research on image stylization, but there are very few studies on selective stylization methods, especially realism. This style of merging objects into stylized scenes has not yet been covered by algorithms; in the film industry, actors are often shot in front of a green screen and then added to other scenes, but this method of production requires a lot of manpower, material resources and financial resources

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
  • Selective image stylizing method based on nonlinear filtering
  • Selective image stylizing method based on nonlinear filtering
  • Selective image stylizing method based on nonlinear filtering

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0024] First define the abbreviations to be used in the following description: Importance Map (Importance Map) is abbreviated as IM, Gaussian deviation edge detection method (Difference of Gaussian), abbreviated as DOG.

[0025] figure 1 It is the basic flow chart of the present invention. The invention uses an image and simple user interaction as input to obtain an output image that harmoniously blends a real object and a stylized scene. The following describes each process of the present invention in detail:

[0026] 1. Simple user interaction

[0027] The user interaction step takes a photorealistic image as input, supplemented by simple user interactions, and aims to output an importance map that marks the importance of each pixel. The present invention provides users with a simple and easy-to-use interactive interface. The user uses a paintbrush to roughly select the object that needs to maintain a sense of reality in the image as the foreground, and the rest is the back...

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

The invention discloses a selective image stylizing method based on nonlinear filtering, which is characterized by comprising the following steps of: (1) simple user interaction; (2) nonlinear filtering; (3) line extraction; and finally output of images which harmoniously combining senses of reality and unreality. In the method, nonlinear diffusion filtering is improved by the following steps of: 1. combining nonlinear diffusion filtering with bilateral filtering; 2. adding a stylizing level control item in an equation; and 3. combining isotropic filtering with anisotropic filtering, so that the nonlinear diffusion filtering can be more suitable for the application of selectivity stylizing. The invention also has the advantages of providing a new artistic style which is an artistic effect of harmonious combination of real objects and stylized scenes, ensuring that a greater contrast is formed between a foreground and a background for giving prominence to the theme of pictures, and being capable of simulating the effect of changing the depth range of fields of a camera.

Description

technical field [0001] The invention relates to a selective image stylization method based on nonlinear filtering. Background technique [0002] The selective image stylization method based on nonlinear filtering belongs to the field of non-realistic image processing. At present, there are many methods for research on image stylization, but there are very few studies on selective stylization methods, especially realism. This style of merging objects into stylized scenes has not yet been covered by algorithms; in the film industry, actors are often shot in front of a green screen and then added to other scenes, but this method of production requires a lot of manpower, material resources and financial resources . Contents of the invention [0003] The technical problem to be solved by the present invention is to provide a selective image stylization method based on nonlinear filtering, which can generate an artistic effect (selective stylization) of fusion of realistic obje...

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 Applications(China)
IPC IPC(8): G06T11/00
Inventor 丛林童若锋唐敏
Owner ZHEJIANG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com