[0034] While high-speed data transmission, other low-speed data or part of high-speed data are often transmitted at the same time. In addition to transmitting images, other sensor data may also be transmitted. The invention provides a method for data transmission using information hiding technology, which has the characteristics of large hiding capacity, high performance and low complexity, and is practical in spacecraft engineering, ground information carrying and transmission systems, and various image transmission systems. value.
[0035] The experiment uses the MATLAB2013a platform, and the carrier data uses 6 512×512 standard grayscale images, such as figure 1 As shown, the secret information is generated with a pseudo-random number generator. If the algorithm needs higher security, chaotic sequences or some encryption algorithms can be used to preprocess the carrier.
[0036] An efficient information hiding method introducing auxiliary pixels of the present invention, the steps are as follows:
[0037] 1) Convert binary secret information to n 2 Base secret information, each secret information is s, and the value of s belongs to the set {0,1,2,...n 2 -1}, n≥2; n can be one of 2, 4, 8, 16
[0038] 2) Generate auxiliary pixel value y, y is [y 0 ,255-y 0 ] Positive integer, where y 0 = N/2 rounded;
[0039] Combine each pixel x and auxiliary pixel y in the carrier image A (size 512*512, 8 bits per pixel) into a pixel pair (x, y), and calculate the function value f=[(n-1)*x+n* y]mod n 2;
[0040] 3) Compare f with secret information s:
[0041] 3.1) If f=s, do not change the pixel pair (x, y), otherwise modify the pixel pair according to the rule of 3.2);
[0042] 3.2) Search for pixel pairs (x+Δx, y+Δy) satisfying f(x+Δx,y+Δy)=s, and select the pixel pair with the smallest modification amount (Δx,Δy) as the dense pixel pair (x' ,y');
[0043] 4) If the secret pixel pair (x', y') overflows, adjust according to formula (1) to obtain a new (x, y), and then re-embed the secret information s;
[0044]
[0045] 5) Repeat steps 3) to 4) until all secret information s is embedded;
[0046] 6) The compressed data set C0 is obtained by combining all Δy into a set and performing lossless compression;
[0047] 7) Produce (y 0 ,255-y 0 ] Positive integer y=y 0 +1 as the auxiliary pixel y, continue to repeat steps 2) to 6) p times to obtain the compressed data set C1, C2...Cp, select the C with the shortest data length from C0, C1 to Cp, and write down the corresponding preferred auxiliary pixel value y; p=0 means no repetition;
[0048] In this example, p=0;
[0049] 8) Send the dense image A'composed of all x', the preferred auxiliary pixel y and the compressed data set C to the receiving end;
[0050] 9) Receive the compressed data set C, decompress to obtain the Δy set, and use y to obtain the set of auxiliary pixels y', that is, y'=y+Δy;
[0051] 10) The x'in the dense image A'and the dense auxiliary pixel y'form a pixel pair (x', y');
[0052] 11) For each pixel pair (x’,y’), according to the formula s=[(n-1)*x’+n*y’]modn 2 Extract every n 2 Base secret information; repeat execution until n 2 The base secret information is extracted;
[0053] 12) will be extracted n 2 The binary secret information is converted into binary secret information. n 2 Take one of 4, 16, 64, 256.
[0054] Performance simulation of the invention
[0055] Use the peak signal to noise ratio (Peak Signal to Noise Ratio, PSNR), hiding capacity C and embedding rate E and other indicators to measure the performance of the hiding algorithm. For an 8-bit digital image with a size of H×W, H and W are positive integers; PSNR is defined as follows:
[0056]
[0057] In the formula, MSE is the mean square error between the original image and the dense image, and the calculation formula is
[0058]
[0059] Here x ij , Represent the pixel value of the original image and the secret image at (i, j) respectively.
[0060] Hidden capacity, embedded rate increase percentage
[0061] T=(V2-V1)/V1*100%=(U2-U1)/U1*100% (2)
[0062] In the formula, V1 represents the embedding rate of the contrast method, V2 represents the embedding rate of the present invention; U1 represents the hiding capacity of the contrast method, and U2 represents the hiding capacity of the present invention.
[0063] Hidden capacity U: the number of hidden bits (bpp) per pixel (8 bits). If Q bits are hidden in Z bits, then the hidden capacity U=8*Q/Z bpp.
[0064] Embedding rate V: Relative hidden capacity or relative value of hidden capacity V, the ratio of the number of hidden bits to the number of carrier bits. If Q bits are hidden in Z bits, the relative hidden capacity is V=Q/Z.
[0065] 1) Comparison of embedding rate and hidden capacity
[0066] In the FEMD method, the parameter n affects the information hiding capacity and the embedding rate. The present invention can further increase the embedding rate by adding auxiliary pixels and optimizing them.
[0067] FEMD method hides one n in 2 pixels (8 bits each, 16 bits in total) on average 2 Base number, the number of bits is K=log 2 (n 2 ); hidden capacity U1=8K/16=K/2bpp, embedding rate V1=K/16;
[0068] The present invention hides one pixel (8 bits) and one auxiliary pixel modification amount d bits on average. 2 Base number, the number of bits is K=log 2 (n 2 ); hidden capacity U2=8K/(8+d)bpp, embedding rate
[0069] V2=K/(8+d), d <8;
[0070] Table 1 shows the comparison results of the hidden capacity and embedding rate of the two methods under different values of n. It can be seen that the hidden capacity U and the embedding rate V of the two methods both increase with the increase of n, when the value of n When increasing from 2 to 16, the hidden capacity of the FEMD method increases from 1bpp to 4bpp, the hidden capacity of the present invention increases from 1.6bpp to 4.9bpp; the embedding rate of the FEMD method increases from 1/8 to 1/2, while the method of the present invention increases The minimum embedding rate has increased from 1/5 to 8/13, which is greater than 1/2.
[0071] Compared with FEMD, the minimum hidden capacity and embedding rate of this method are improved by 23%-60%. This is because for the same carrier, the auxiliary pixel value y is the same, and the coding bit number of the auxiliary pixel after the secret information is embedded is only determined by its modification amount, which can be used (1+log 2 n)bit means that the number of bits is obviously less than 8 bits.
[0072] Table 1 The hidden capacity U and embedding rate V of the two methods with different values of n
[0073]
[0074] Note: The hidden capacity U and the embedding rate V are calculated without considering the optimal compression. After considering the optimized compression, the number of coding bits of the auxiliary pixel embedded with the secret information is only determined by the amount of modification, not at all (1+log 2 n)bit means that the average number of bits is much smaller than 8 bits of the carrier. After compression, the total number of bits may be reduced by several times to 100 times, or even thousands of times. If the modification amount of the auxiliary pixel y=0, the auxiliary data is compressed The amount of data is very small, which is equivalent to d=0. The hidden capacity can even be doubled.
[0075] 2) PSNR comparison
[0076] In order to measure the degree of improvement in image quality of the present invention, Table 2 shows the image quality obtained by the present invention and the FEMD method under different embedding rates V. On the whole, under the same or higher embedding rate or hidden capacity, the PSNR of the present invention is higher than that of the FEMD method. For example, at the same embedding rate (1/2), the average PSNR is increased from 34.84dB to 41.97dB, the average improvement 7.13dB.
[0077] In addition, even when 8/13 (greater than 1/2) secret information is embedded, the PSNR of the present invention is still as high as 35.71dB, indicating that the method is an efficient information hiding algorithm, and the auxiliary pixel value as a key can ensure the secret information safety.
[0078] Table 2 PSNR (dB) of two methods at different embedding rates
[0079]
[0080] 3) Compare with other similar methods
[0081] In order to compare this algorithm with other similar methods and compare the Lena image hiding effect, the present invention can realize more information hiding with different embedding rates, and the PSNR of the present invention is better than the LSB method. For example, when n=2, PSNR is increased by at least 2.0dB.
[0082] The reason for the improvement of image quality is that the present invention can greatly increase the information embedding rate by adding auxiliary pixels. Compared with the FEMD method, when embedding the same proportion of secret information, the present invention needs to use a lower pixel comparison ratio, thus reducing the modification rate of the carrier. small.
[0083] In short, the present invention proposes an efficient information hiding method that introduces auxiliary pixels. The hiding capacity has nothing to do with the type of original data. It can be image data or other data. The amount of hiding is always fixed, with large hiding capacity and information security. , And easy to implement by software and hardware. Its characteristic is that the method realizes the joint processing of secret information and key through the introduction of auxiliary pixels and data optimization, and the receiving end can completely restore the secret information and restore the original data with high quality.
[0084] This method can hide information in each pixel of the original image data, improve the efficiency of hiding, and break through the current method of hiding in one pixel pair (two pixels). It can reach or exceed 1/2 of any image. The hidden capacity, when the hidden capacity is 1/2, the PSNR of the restored carrier image exceeds 41dB, and the performance is better than typical hidden methods such as LSB and FEMD hidden methods.
[0085] The parts of the present invention that are not described in detail belong to the common knowledge of those skilled in the art.
