藏密學是用於資訊隱藏的一種技術，隨著網路通訊的持續成長，
愈益凸顯它的重要性。最近幾年，陸續有各種不同的藏密演算法被提
出。例如，Ni 等人就提出了一種基於修改直方圖上的無失真資料隱
藏演算法。
為了增加隱密性和資訊能夠嵌入的容量，我們用亂數排列與直方
圖重新量化的方式來延伸Ni 所提出的演算法。藉著亂數排列，它不
再容易被暴力法所破解；藉由直方圖重新量化，我們可以增加三倍的
資訊嵌入量。同時，在我們的方法下，視覺無法分辨圖像在嵌入資訊
前後的差異性。

Steganography is a technique of information hiding. It is more and more
important while the internet communication grows up. Various steganographic
algorithms have been proposed in recent years. For example, Ni et al. have proposed a
lossless data-hiding algorithm based on the histogram modification.
To have more security and more information embedding capacity, we extend the
Ni’s algorithm with a random permutation and a histogram re-quantization. With a
random permutation, it is not easy to be broken by a brute-force attack. With a
histogram re-quantization, we increase the embedding capacity about 3 times. In our
approach, it is visually indistinguishable between a cover image and a stego-image
with a large embedding capacity.

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