用Python分形图像缩放 [英] Fractal image scaling with Python

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本文介绍了用Python分形图像缩放的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我处于提供相对低分辨率图像的位置(通过API,无法获得更高分辨率的图像),并且需要生成高分辨率图像。

I am in a position where relatively low resolution images are provided (via an API, higher resolution images are not available) and high resolution images need to be generated.

我看过 PIL 它对于所有事情都很棒...除了放大图像。

I've taken a look at PIL and it's just great for about everything... Except scaling up images.

它有共同的调整算法大小


  • 最近邻

  • Bilinear

  • Bicubic

  • 消除锯齿

  • Nearest Neighbor
  • Bilinear
  • Bicubic
  • Anti-aliased

我想使用Fractal Resizing(根据杰夫关于编码恐怖的帖子),但唉,PIL不支持这种调整大小。

I would like to use Fractal Resizing (as per jeff's post on coding horror), but alas, PIL has no support for this kind of resizing.

进一步谷歌搜索yiel d没有替代库可以提供分形图像调整大小。

Further Google searches yield no alternative libraries to provide fractal image resizing either.

这样的事情是否存在或者我是否真的需要扣下并写下我自己的分形调整算法?

Does such a thing exist or do I really have to buckle down and write my own fractal resizing algorithm?

我不是专家,但从我目前的优势来看,这看起来像是一个相当陡峭的学习曲线:(

I'm no expert but from my current vantage point, that looks like a pretty steep learning curve :(

如果没有这样的库存在,也许你有一些建议在哪里学习分形压缩算法?

If no such library exists, maybe you have some advice where to learn about fractal compression algorithms?

推荐答案

有算法,而你'绝对不会在Python中找到它们。首先,您可以参考这篇论文:

There are algorithms, and you're definitely not going to find them in Python. To start with, you can take this paper:

Daniel Glasner,Shai Bagon和Michal Irani,单一图像中的超分辨率,在IEEE会议论文集中计算机视觉国际会议,日本京都,2009年。

Daniel Glasner, Shai Bagon, and Michal Irani, "Super-Resolution from a Single Image," in Proceedings of the IEEE International Conference on Computer Vision, Kyoto, Japan, 2009.

这是非常先进的,非常复杂的,并且产生了有希望的结果。如果您将其变为python实现,请将其发布给公众:)

It is very much state of the art, highly sophisticated, and producing promising results. If you ever make it into a python implementation please release it to the public :)

这篇关于用Python分形图像缩放的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!

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