The Experts below are selected from a list of 2559 Experts worldwide ranked by ideXlab platform

Chen Hong - One of the best experts on this subject based on the ideXlab platform.

  • An Image Compression Based on Wavelet Zerotree
    Information & Computation, 2004
    Co-Authors: Chen Hong
    Abstract:

    An Image compression method based on the features of Image wavelet decomposition coefficient and zerotree structure is proposed in this paper. The matrix of wavelet Image and the multiresolution matrix elements are depicted too. The encoding structure and the expressions which calculate the maximal absolute value of each subband wavelet coefficient and the mean square error ignoring this subband are given. With a Lena Image of 512×512×8, the simulation is carried out. The results are compared with those of EZW. With the same peak signal to noise ratio(PSNR), this method gains obviously higher compression ratio and has better performance.

Hafiz Muhammad Waseem - One of the best experts on this subject based on the ideXlab platform.

Bin Yang - One of the best experts on this subject based on the ideXlab platform.

  • Adaptive reversible data hiding scheme based on integer transform
    Signal Processing, 2012
    Co-Authors: Fei Peng, Bin Yang
    Abstract:

    In this paper, we present a new reversible data hiding algorithm based on integer transform and adaptive embedding. According to the Image block type determined by the pre-estimated distortion, the parameter in integer transform is adaptively selected in different blocks. This allows embedding more data bits into smooth blocks while avoiding large distortion generated by noisy ones, and thus enables very high capacity with good Image quality. For instance, by the proposed method, we can embed as high as 2.17bits per pixel into Lena Image with a reasonable PSNR of 20.71dB. Experimental results demonstrate that the proposed method outperforms some state-of-the-art algorithms, especially for high capacity case.

A. G. Ananth - One of the best experts on this subject based on the ideXlab platform.

  • FRACTAL Image COMPRESSION USING QUADTREE DECOMPOSITION AND HUFFMAN CODING
    2012
    Co-Authors: A. G. Ananth
    Abstract:

    Fractal Image compression can be obtained by dividing the original grey level Image into unoverlapped blocks depending on a threshold value and the well known techniques of Quadtree decomposition. By using threshold value of 0.2 and Huffman coding for encoding and decoding of the Image these techniques have been applied for the compression of satellite Imageries. The compression ratio (CR) and Peak Signal to Noise Ratio (PSNR) values are determined for three types of Images namely standard Lena Image, Satellite Rural Image and Satellite Urban Image. The Matlab simulation results show that for the Quad tree decomposition approach shows very significant improvement in the compression ratios and PSNR values derived from the fractal compression with range block and iterations technique. The results indicate that for a Lena Image C R is 2.02 and PSNR values is 29.92, Satellite Rural Image 3.08 and 29.34, Satellite urban Image 5.99 and 28.12 respectively The results are presented and discussed in this paper.

  • ANALYSIS OF SPIHT ALGORITHM FOR SATELLITE Image COMPRESSION
    Advanced Computing: An International Journal, 2011
    Co-Authors: K Nagamani, A. G. Ananth
    Abstract:

    Wavelets offer an elegant technique for representing the levels of details present in an Image. When an Image is decomposed using wavelets, the high pass component carry less information, and vice-versa. The possibility of elimination of the high pass components gives higher compression ratio in the case of wavelet based Image compression. To achieve higher compression ratio, various coding schemes have been used. Some of the well known coding algorithms are EZW (Embedded Zero-tree Wavelet), SPIHT (Set Partitioning in Hierarchical Tree) and EBCOT (Embedded Block Coding with Optimal Truncation). SPIHT has been one of the popular schemes used for Image compression. In this paper the performance of the SPIHT (Set Partitioning in Hierarchical Trees) compression technique for satellite Images are studied. The satellite rural and urban Images have been used for the present analysis. The standard Lena Image is used for the purpose of comparison. For a given compression ratio, the PSNR (peak signal to noise ratio) values are computed to evaluate the quality of the reconstructed Image. The analysis carried out clearly suggests that the PSNR values increases with the level of decomposition. For the satellite Images the PSNR values achievable are less compared to that of Standard Lena Image and the SPIHT Algorithm are better suited for compression of Satellite urban Images.

  • Study of EZW compression techniques for high and low resolution satellite Imageries
    2010 Second International conference on Computing Communication and Networking Technologies, 2010
    Co-Authors: K Nagamani, A. G. Ananth
    Abstract:

    Image compression methods employing wavelet transforms have been successfully implemented to provide high compression rates while maintaining good Image quality. The main contribution of wavelet theory and multi-resolution analysis is that, it provides an elegant framework in which both anomalies (such as edges and object boundaries) and trends (areas of high statistical spatial correlation) can be analyzed on an equal footing This results in a considerable improvement in encoding the significance map, and hence, a higher efficiency in compression. By employing the Successive approximation entropy coded quantization (SAQ), the EZW (Embedded Zero-tree Wavelet) coder generates a representation of the Image that is coarser-to-finer in both the spatial domain and frequency domain simultaneously. Applying the DWT coefficients and EZW techniques using five threshold values, the maximum compression ratios achieved for an acceptable quality of the Image have derived. The three types of Images Lena Image and high resolution urban Image (SatUImg and low resolution Rural (SatRImg) Image have been considered for the analysis. The results show that for the standard Lena Image one can achieve highest compression ratios (~11.28). where as the Rural Images (SatRImg) shows better compression ratio (~5.75) compared to that of Urban Images (satUImg) which is small (~1.39). The results are presented and discussed in the paper.

Majid Khan - One of the best experts on this subject based on the ideXlab platform.