感知图像下采样 [英] Perceptual Image Downsampling

问题描述

因此​​，这里是我的问题：

So here is my problem:

我有一个图像，该图像是大的（高分辨率）和它需要是小的（低得多的分辨率）。

I have an image, that image is large (high resolution) and it needs to be small (much lower resolution).

所以，我做的天真的事情（每杀死一个像素），结果看起来很差。

So I do the naive thing (kill every other pixel) and the result looks poor.

所以，我尝试做一些更聪明（使用傅立叶变换和重新采样的傅立叶空间低通滤波），结果是好一点，但仍然相当差。

So I try to do something more intelligent (low pass filtering using a Fourier transform and re-sampling in Fourier space) and the result is a little better but still fairly poor.

所以我的问题，是有感知动机的图像向下采样算法（或执行）？

So my question, is there a perceptually motivated image down-sampling algorithm (or implementation)?

编辑： 虽然我知道了一些重采样技术，我的应用程序更关心的是preserving感知特征，而不是产生平滑的图像。

edit: While I am aware of a number of resampling techniques, my application is more concerned with preserving the perceptual features, rather than producing smooth images.

EDIT2：它是安全的假设我有熟悉的数字信号处理，卷积，小波变换等某种程度的

edit2: it is safe to assume I have some level of familiarity with digital signal processing, convolutions, wavelet transforms, etc

推荐答案

双立方插值通常被视为不够好，但目前还没有完美的解决方案，它取决于人对图片的属性被重新采样。

Bicubic interpolation is generally regarded as good enough, but there is no perfect solution, it depends on people and on the properties of the picture being resampled.

相关链接：

我甚至不知道，锐度也被称为锐度。

I didn't even know that sharpness was also called acutance.

别名是下采样天真地时可能发生的问题。

Aliasing is a problem that can occur when downsampling naively.

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