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

Multi-exposure image fusion method of automatically removing ghosts

An image fusion, multi-exposure technology, applied in image enhancement, image analysis, image data processing and other directions, can solve the problems of inconsistent brightness in moving areas, unsuitable for real-time applications, easy residual ghosts, etc., to achieve good visual effects, remove ghosts, etc. Shadow phenomenon, simple method

Active Publication Date: 2018-08-17
ZHEJIANG UNIV
View PDF2 Cites 15 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The current multi-exposure fusion method for ghosting is complex in calculation and takes a long time, which is not suitable for real-time applications. Inconsistencies in brightness around edges

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
  • Multi-exposure image fusion method of automatically removing ghosts
  • Multi-exposure image fusion method of automatically removing ghosts
  • Multi-exposure image fusion method of automatically removing ghosts

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0040] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0041] Aiming at multi-exposure fusion of shooting scenes with moving objects, the present invention uses gradient domain weighted optimization to automatically remove ghost images, and uses block-based multi-exposure fusion method to fuse multiple input LDR images to preserve image details. The process of the present invention is as attached figure 1 As shown, it mainly includes three steps: motion region detection, latent image generation, and multi-exposure fusion.

[0042] Step 1. Motion Region Detection

[0043] 1-1 Input multiple LDR images with different exposure times, and select the input image with the middle exposure time as the reference image. Calculate the difference between a reference image and other input images using bidirectional luminance mapping

[0044]

[0045] where L n is the input image, L ref For the reference i...

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 multi-exposure image fusion method of automatically removing ghosts. The multi-exposure image fusion method of automatically removing ghosts provides an effective method of moving object selection, for the phenomenon that ghosts exist in multi-exposure image fusion of a dynamic scene. The multi-exposure image fusion method of automatically removing ghosts includes the steps: selecting one input LDR image as a reference image, detecting the motion area by means of a method of bidirectional luminance mapping, calculating the motion weight, and automatically removing theghosts by means of a method of gradient domain weighted optimization so as to obtain a latent image; and after removing the ghosts, calculating the fusion weight by means of the fusion method based on blocks, performing exposure fusion, maintaining the detailed information and suppressing the abnormal value. The multi-exposure image fusion method of automatically removing ghosts can effectively maintain the details of a plurality of input images and remove the ghosts, can avoid complicated parameter setting and arbitrariness for a user to set the threshold, and has higher robustness for the ghost phenomenon in various scenes.

Description

technical field [0001] The invention belongs to the field of digital image processing, and relates to a multi-exposure image fusion method for automatically removing ghost images. Background technique [0002] The real-world dynamic range is high, and direct acquisition of high-dynamic-range images requires a professional-grade high-dynamic-range camera, and most imaging devices cannot capture such a high dynamic range. High Dynamic Range Imaging (HDRI) is an efficient method of acquiring high dynamic range images by acquiring a series of low dynamic range images (LDR) at different exposures and then synthesizing an HDR image. This method only needs ordinary imaging equipment to complete, so it is widely used. However, due to camera shake or object motion in the scene, the results obtained by these direct synthesis methods have ghosts orghosting artifacts. The anti-ghosting HDR synthesis technology can use multiple LDR images to synthesize HDR images, and at the same time ...

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
IPC IPC(8): G06T5/00G06T5/50
CPCG06T5/50G06T2207/10024G06T2207/20016G06T2207/20208G06T2207/20221G06T5/73
Inventor 冯华君常猛徐之海李奇陈跃庭
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