Prediction error based secret image transmission over radio mobile channel

Author(s):  
Tapasi Bhattacharjee ◽  
Santi P. Maity ◽  
Apurba Roy
2010 ◽  
Vol E93-D (2) ◽  
pp. 399-402 ◽  
Author(s):  
Shih-Chieh SHIE ◽  
Ji-Han JIANG ◽  
Long-Tai CHEN ◽  
Zeng-Hui HUANG

2018 ◽  
Vol 7 (3.6) ◽  
pp. 110
Author(s):  
C Narmatha ◽  
P Manimegalai ◽  
S Manimurugan ◽  
Saad Almutairi ◽  
Majed Aborokbah

This paper presents aMSI(Modified Steganography for Image) decode technique for the perfect reconstruction process. Many algorithms are failing in decoding process due to the various reasons. In order to overcome those issues, an efficient decode process of MSI has been proposed in this paper presents. Basically, theMSImethod can be classified into two parts of Encode and Decode. The segregation process for constructing the subbands,8-bit binary conversion process, Inverse substitution process and Decimal conversion process are doing an important role inMSIdecode process. In addition, to measure theMSIdecode performances, the standard parameters are used. This technique is designed mainly for the secret medical image transmission. The secret input image pixels should not be loss while transmitting over the network. In case of loss, it’s very hard to retrieve the original secret image/date during the reconstruction process. This issue has been addressed byMSIdecode process. In result, the original secret image can be restored 100% from this technique, the decode time is minimum than the conventional methods, the replica of the cover or known image can be obtained. However, the main advantages of this technique are easy to handle, more complex and strength than other methods, a perfect reconstruction without any loss and less execution time.  


2020 ◽  
Vol 309 ◽  
pp. 01008
Author(s):  
Ji Zhang ◽  
Haibo Ruan ◽  
Dongsheng Hu

Image transmission is very important for various applications. In order to ensure the security of image transmission, a novel image transmission method based on mosaic image creation and secret image recovery is proposed. The proposed method has two phases: 1) Mosaic image creation. A mosaic image is generated, which includes the fragments of an input secret image with color corrections according to a similarity criterion based on color variations. 2) Secret image recovery. Based on the received signal, the secret image is recovered losslessly from the generated mosaic image. Experimental results show that the proposed method has better feasibility.


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