SIS for (k, k) Threshold Based on CRT and Image Characteristics 175
Lin’s research, some researchers [4,12] developed more Shamir’s polynomial-
based schemes to receive more features. Although Shamir’s polynomial-based
SIS only needs k shadow images for decoding the distortion-less secret image,
it is in general lossy recovery with auxiliary encryption and high computation
complexity. On account of the secret is decoded modulo 251 which is less than
maximum pixel value 255, the recovery image will be lost when the pixel value of
the secret image is larger than 251 so that Shamir’s polynomial-based SIS owes a
little bit of loss. Image encryption is usually utilized before sharing that results in
auxiliary encryption. Because of Lagrange interpolations in the recovery phase,
it needs O(k log
2
k) operations [1], i.e., complicated computations.
CRTSIS overall can achieve the advantages of lossless recovery, no auxiliary
encryption and lower recovery computation complexity (the modular only O(k)
operations [1]), so that which is discussed by other researchers [2,3,6,8,10].
Related works of CRTSIS are analyzed as follows. Yan et al. firstly [10]dis-
cussed CRT in SIS, which may deduce a little information leakage and may be
lossy. Shyu and Chen [6] put forward a threshold CRTSIS utilizing Mignotte’s
scheme based on pseudo random number generator which suffers from auxiliary
encryption. Ulutas et al. [8] investigated a modified SIS using Asmuth Bloom’s
secret sharing scheme through dividing the grayscale image pixel values into
more possible intervals. It fails to consider pixel value 2 times or more to the
parameter, which may lead to lossy recovery. Chunqiang et al. [3] designated
a CRTSIS employing the chaotic map which results in auxiliary encryption.
Chuang et al. [2] gave a simple CRTSIS and examined (3, 5) threshold for RGB
color images. Their method has the limitation of lossy or least significant bits
pre-stored. In addition, their algorithm parameters condition is different from the
adopted explicit parameters in the experiment. Finally, most existing CRTSIS
schemes fail to provide applicable explicit parameters for the implementations
based on the image characteristics. As a result, traditional CRTSIS methods
overall suffer from auxiliary encryption, lossy recovery and ignoring the image
characteristics, which are caused by that their ideas are borrowed from secret
data sharing.
According to image characteristics and CRT, in this paper we propose a CRT-
SIS method for (k, k) threshold, through enlarging the grayscale image pixel
values. Our method owns the benefits of no auxiliary encryption and lossless
recovery for grayscale image. The contributions of this paper are that, according
to the image characteristics, our (k, k) threshold CRTSIS for grayscale image is
lossless recovery without auxiliary encryption. Furthermore, we provide explicit
parameters for the implementations based on image pixel value range. We per-
form experiments and analysis to illustrate our effectiveness.
The rest of the paper is organized as follows. Section 2 introduces some basic
requirements for the proposed method. In Sect. 3, our method is presented in
detail. Section 4 is devoted to experimental results. Finally, Sect. 5 concludes
this paper.