（2）不可逆压缩 不可逆压缩就是有失真（Lossy）编码，信息论中叫熵压缩（Entropy compression）。熵压缩的一个简单例子就是在检测采样值时设置某个门限（阈值）： 只有当采样值超过指定的门限时才传输数据。
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Finally, information theory is concerned with the amount of data that can be stored on a given medium, and hence deals with concepts such as compression and entropy.
最后，信息理论关注的是，可以在给定的介质存储的数据量，从而处理如压缩和熵的概念。
Lossless compression bounds of images naturally acquired by various imaging sensors are estimated using a practical method based on multi scale conditional entropy and memory measurement.
为估计利用各类成像传感器自然获取图像的无损压缩极限，提出一个利用多尺度条件熵和记忆性度量的实用方法。
The paper analyses the weakness of traditional speed-up techniques for image fractal compression firstly, and proposes a novel idea by using entropy to improve image fractal compress performance.
本文首先分析图像分形压缩技术中传统加速方法的性能缺陷，随后提出使用图像块的熵值来改进分形压缩性能的思想。
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