image-quilting

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A numpy implementation of the paper "Image Quilting for Texture Synthesis and Transfer" (2001)

image-quilting 최신버젼 다운로드

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# Image Quilting for Texture Synthesis and Transfer

![Demo](https://raw.githubusercontent.com/axu2/image-quilting/master/abstract_screenshot.PNG)

https://www.youtube.com/watch?v=QMiCNJofJUk

Image quilting is a technique of generating new images 
by stitching together patches of existing images.
It has applications of

1) Texture synthesis, generating arbitrarily large textures from small real-world samples and

2) Texture transfer, re-rendering an image in the style of another.

>The method
works directly on the images and does not require 3D information.

For more information, consult the original paper at https://people.eecs.berkeley.edu/~efros/research/quilting.html

All images in this readme come from the original paper or presentation at SIGGRAPH '01.

In this repository, we will be implementing the paper using Python and NumPy.

## Texture Synthesis

The algorithm starts with an input image and a block size:

![input block](https://raw.githubusercontent.com/axu2/image-quilting/master/input.png)

We then define a minimum cost path between the overlap of two blocks:

We then build up a synthesized image by tiling small blocks of the input image.

![build](https://raw.githubusercontent.com/axu2/image-quilting/master/build.png)

(a) Here, we just randomly choose blocks

(b) Here we pick blocks that have the least overlap error

(c) We do everything in (b) but also cut along the minimum error boundary.

## Texture Transfer

>[Here] just add another constraint when sampling: similarity to underlying image at that spot

![half](https://raw.githubusercontent.com/axu2/image-quilting/master/half.png)