在目前漸進式視覺機密分享（PVSS）的研究中，Wang et al.（2007）和 Wang（2009）都是採用逐步還原不同機密影像區塊的方式來進行，不過在他們所提出的分享模式中，都會產生分享矩陣的設計沒有規律性、浪費儲存空間、還原影像品質不佳，以及不適合應用於灰階或彩色影像等缺點。為了解決上述的缺點，本研究提出一個應用影像區塊進行漸進式還原的非擴展式視覺機密分享模型，稱之為 Block-basedProgressive Visual Secret Sharing（BPVSS）。其做法是將機密影像切割成 n 個不重疊的影像區塊，當重疊 t（2 ≤ t ≤ n）張投影片後，疊合影像上會有 t 個影像區塊內的機密內容會被完全還原。相較於其他學者的研究成果，本研究具備下列幾項優點：1本研究的分享模型的概念簡明、容易實作，並且參與機密資訊分享的人數不會受到限制。2 在分享投影片為雜訊式的內容時，還原影像上可以產生出 50% 的黑白色差，使得機密資訊能清楚地為人眼所辨識。3 分享投影片也可以轉換成有意義的偽裝影像，因此可以提高分享投影片的安全性，並且在偽裝影像與還原影像上皆有 25% 的黑白色差。4 本研究的機密影像適用於灰階與彩色影像。5 每一張分享投影片大小皆與機密影像相同，不需要擴展。

In the related works of progressive visual secret sharing (PVSS), Wang et al. (2007)and Wang (2009) all have the following drawbacks: (1) The design of the dispatchingmatrices is not regular. (2) Shares are m-times larger than the original secret image. (3)Restored image’s quality is poor. (4) Their schemes are not suitable to apply in grayscaleand color secret images. In order to solve the above limitations, we propose a nonexpandedPVSS approach, in which the recovery method is based on secret blocks, namelyBlock-based Progressive Visual Secret Sharing (BPVSS). We divide a secret image inton non-overlapped image blocks, and an additional portion of secret will be restored aftersuperimposing one more transparency. When superimposing any t shares, there have t(2 ≤ t ≤ n) secret blocks being restored. Compared with other related works, BPVSS hasseveral advantages: (1) The concept of this model is concise, easy to implement, and thenumber of participants will not be restricted. (2) In the situation of noise-like shares, thecontrast of the restored image is 50%, which means that the hidden message can be clearlyrecognized by the naked eyes. (3) When transparencies are shifted from noise-like intomeaningful, the contrast of the stego-image and the restored image will be 25% which isstill superior to other related studies. (4) Our scheme is more suitable for grayscale andcolor secret images than previous related studies. (5) The size of transparencies is the same as the size of secret image.