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Efficient and Effective Compression Algorithm for Infrared (IR) Image Based on Wavelet
Efficient and Effective Compression Algorithm for Infrared (IR) Image Based on Wavelet
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机译：基于小波的红外图像高效压缩算法
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#$%^&*AU2013100575A420130606.pdf#####Abstract Infrared (IR) imaging techniques have been used extensively for military and civilian purposes, in particular in dark conditions. However, there is an important and popular process always to be involved, which is enormous data to be stored and transmitted during various applications. Many algorithms have been proposed to improve the performance of the compression scheme. In this patent we extended a traditional wavelet algorithm to an IR image compression with updated technology. It is compared our proposed algorithm, in terms of performance, with others related methods based on the standard parameters. It is well known that the technology of lifting based Cohen-Daubechies-Feauveau wavelets with the low-pass filters of the length 9 and 7 (CDF 9/7) wavelet transform is very efficient and effective in image compression. In our proposed algorithm, this technology will be coupled with Set Partition in Hierarchical Trees (SPIHT) coding algorithm and entropy coding techniques. One of our contributions in this patent is to demonstrate the choice of decomposition level, which is playing a very important role in achieving superior wavelet compression performances. An IR image quality is assessed objectively by the standard parameters, such as compression ratio, peak signal-to-noise ratio (PSNR), mean structural similarity index (MSSIM). It is also evaluated subjectively by using perceived image quality. It is to be supported by the simulation results that for our proposed algorithm are superior to others such as the compression ratio has been significantly improved by 88%, together with highest PSNR values and MSSIM which are close to 1. It is also found that the best decomposition level and required bit rate per pixel for infrared (IR) images in our algorithm. Keywords: IR, PSNR, MSSIM, SPIHT, Entropy coding.FIGURES Figure 1: Proposed image compression block diagram Spliting Lifting IScaling Figure 2: The lifting-based Wavelet Transform Figure 3: Lifting implementation of the analysis side of the CDF 9/7 filter bank
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