• Matlab
  • Simulink
  • NS3
  • OMNET++
  • NS2

Super Resolution Image Reconstruction

In this paper we present a novel algorithm based on Super-Resolution Image Reconstruction (SRIR). We use pattern recognition method to optimize the performance of digital watermarking. First, the binarywatermarking is scanned to one-dimension sequence before embedding, at the same time, we chose a mixed error-correcting code-(3,1,2)convolutional code and (3,1) repetition code to encode the originalwatermarking, and the sequence is inputted into the (3,1,2) convolution encoder and (3,1) repetition encoder frame by frame. The output sequence is scanned to some matrixes as the watermarking information.

Second, the super-resolution reconstruction of image sparse representation is implemented on carrier image. Then, block the image and the watermarking which is encoded with mixed error-correcting code is embedded in low frequency band of the Discrete Wavelet Transform (DWT) repeatedly. Experimental results show that our imagewatermarking scheme with SRIR is better than the traditional one which is without SRIR, not only invisible, but also robust against various common signal processing (such as JPEG compression, salt and pepper noise, Gaussian low-pass filtering, and median filtering).

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