Digital Image Processing

P. Vetrivelan ¹, Kandaswamy Arumugam ²

Affiliations
1 Department of Electronics and Communication Engineering, Sri Ramakrishna Institute of Technology, Coimbatore, IN
2 Department of Bio Medical Engineering, PSG College of Technology, Coimbatore, IN

Abstract

The main aim of this paper is to hide the digital data or a digital image into another image using a Contourlet transform. In order to obtain Contourlet transform, the original image is divided into low and high frequency images by using Laplacian pyramid and directional filter bank. Since the datas can be hidden only on low frequency images, the high frequency is again divided into number of sub bands using directional filter bank. Hence by combining these sub bands, Contourlet coefficients can be obtained. Then by applying inverse Laplacian and inverse directional filter bank to these sub bands the reconstructed image is obtained. Thus Contourlet coefficients are found next is to watermark the resultant image, by embedding and retrieving method.
Finally, the difference and watermarked image is displayed. From this it is possible to compute PSNR and MSE values. It finds its application in secret communication systems, the robustness against noise and data rate is the most important feature, while for data authentication, imperceptibility and robustness against different processing attacks are the most significant ones.

Keywords

CT-Contourlet Transform, DWT-Discrete Wavelet Transform, LP-Laplacian Pyramid, DFB-Directional Filter Bank, PDFB-Pyramid Directional Filter Bank, VQ-Vector Quantization, PSNR-Peak to Signal Noise Ratio, MSE-Mean Square Error.

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P. Vetrivelan ¹, A. Kandaswamy ²

Affiliations
1 Sri Ramakrishna Institute of Technology, IN
2 Bio-Medical Engineering Department, PSG College of Technology, Coimbatore, Tamilnadu, IN

Abstract

This paper discuss the compression of an image using lifting scheme to implement SPIHT (set partitioning of hierarchical trees). The SPIHT algorithm uses dynamic data structure that does not make it possible for use in a hardware system. Here the implementation of SPIHT algorithm using lifting scheme in system c is done, so that it becomes suitable for implementation in FPGA. The hardware implementation is done in a XILINX XC3S500E device.

Keywords

Discrete Wavelet Transform, SPIHT, Lifting Scheme, Image Compression.

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