https://github.com/pandeykartikey/multi-focus-image-fusion-via-gcf

Python implementation of the paper "Fusion of multi-focus images via a Gaussian curvature filter and synthetic focusing degree criterion"
https://github.com/pandeykartikey/multi-focus-image-fusion-via-gcf

feature-extraction gaussian-filter image-fusion image-processing

Last synced: about 2 months ago
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Python implementation of the paper "Fusion of multi-focus images via a Gaussian curvature filter and synthetic focusing degree criterion"

• Host: GitHub
• URL: https://github.com/pandeykartikey/multi-focus-image-fusion-via-gcf
• Owner: pandeykartikey
• Created: 2019-03-05T18:00:17.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2019-05-04T05:41:37.000Z (about 6 years ago)
• Last Synced: 2025-04-01T16:52:51.216Z (3 months ago)
• Topics: feature-extraction, gaussian-filter, image-fusion, image-processing
• Language: Python
• Homepage:
• Size: 1.3 MB
• Stars: 19
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Multi-Focus Image Fusion via GCF

The main objective which is to realize a system to convert a set of multi-focused images to a clear image is achieved by using a GCF and a synthetic FDC(Focusing Degree Criterion). The algorithm for the same includes the following steps:

- Feature Extraction (using Gaussian Curvature Filter)

- Focusing Degree Confirmation (using Spatial Frequency and Local Variance)

- Filtering Coarse fusion map

- Image Fusion

### Usage

```

usage: fusion.py [-h] [--image1path IMAGE1PATH] [--image2path IMAGE2PATH]

                 [--color COLOR] [-m M] [-n N] [-p P] [-q Q]

                 [--outputdir OUTPUTDIR]

arguments:

  -h, --help            show this help message and exit

  --image1path IMAGE1PATH

                        Path to the Image 1.

  --image2path IMAGE2PATH

                        Path to the Image 2.

  --color COLOR         Whether the image is colored or not

  -m M                  no. of times gaussian curvature filter is applied

  -n N                  dialation and erosion kernel size

  -p P                  pxq dimension of patch in focus region

  -q Q                  pxq dimension of patch in focus region

  --outputdir OUTPUTDIR

                        Directory in which output needs to be stored

```

### Image Fusion Pipeline

![Pipeline](./pipeline.png "Pipeline")

### Result

![Result](./result.png "Result")