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项目描述

GREYCstoration is an image regularization
algorithm that processes an image by locally
removing small variations of pixel intensities
while preserving significant global image
features, such as sharp edges and corners.
The most direct application is denoising. By
extension, it can also be used to inpaint or
resize images. It is based on methods using
nonlinear multi-valued diffusion PDEs (Partial
Differential Equations) for image
regularization. This kind of method generally
outperforms basic image filtering techniques
(such as convolution, median filtering, etc.)
classically encountered in painting programs.
Other image denoising plugins are available,
but are not free, and the corresponding
algorithms are kept secret.

系统要求

System requirement is not defined
Information regarding Project Releases and Project Resources. Note that the information here is a quote from Freecode.com page, and the downloads themselves may not be hosted on OSDN.

2006-03-27 16:36
2.3

正规化算法得到改进,现在快3倍执行比以前的版本。阿边缘增强滤波器加入,使更多的大幅恢复图像。包含空格的文件名与一些缺陷已得到纠正。
标签: Major feature enhancements
The regularization algorithm has been improved and
now performs three times faster than previous
versions. A edge-enhancement filter was added,
allowing more sharply restored images. Some bugs
with filenames containing spaces have been
corrected.

2006-02-11 09:57
2.2

该算法是现在冷杉给予一个去噪质量标准(即'峰值信噪比')去噪后已被一个由用户人为损坏的图像。这使得与其他现有的去噪方法的数值比较。该接口已修改为显示原始,嘈杂,恢复图像时,用户已损坏人工噪声的图像。
标签: Minor feature enhancements
The algorithm is now ables to give a denoising quality criterion (the 'Peak Signal to Noise Ratio') after denoising an image that has been
artificially corrupted by the user. This allows
a numerical comparison with other existing denoising methods. The interface was modified to show the original, noisy, and
restored images when the user has corrupted the image with artificial noise.

2006-02-07 02:32
2.1

标签: Initial freshmeat announcement

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