【摘要】：為了提高圖像壓縮質(zhì)量,針對(duì)傳統(tǒng)壓縮算法的不足,提出一種曲波變換和最小二乘支持向量機(jī)相融合的圖像壓縮算法。首先采用曲波變換把圖像分解為不同尺度和不同方向的曲波系數(shù),并采用熵編碼對(duì)粗尺度層曲波系數(shù)進(jìn)行壓縮,然后利用最小二乘支持向量機(jī)對(duì)細(xì)尺度層中不同方向的曲波系數(shù)進(jìn)行學(xué)習(xí),并通過和聲搜索算法優(yōu)化最小二乘支持向量機(jī),實(shí)現(xiàn)細(xì)尺度層曲波數(shù)的壓縮,最后采用圖像壓縮仿真實(shí)驗(yàn)測(cè)試其性能。結(jié)果表明,曲波變換和最小二乘支持向量機(jī)相融合的圖像壓縮算法提高了圖像壓縮的峰值信噪比,加快了圖像壓縮的速度,獲得了更好的圖像壓縮效果。
[Abstract]:In order to improve the quality of image compression, an image compression algorithm based on curved wave transform and least square support vector machine is proposed to overcome the shortcomings of traditional compression algorithms. Firstly, the curved wave transform is used to decompose the image into curved wave coefficients of different scales and directions, and entropy coding is used to compress the curved wave coefficients of rough scale layer. Then, the curved wave coefficients in different directions in fine scale layer are learned by least square support vector machine, and the least square support vector machine is optimized by harmony search algorithm to realize the compression of curved wave number of fine scale layer. Finally, the performance of the image compression simulation experiment is tested. The results show that the image compression algorithm based on curved wave transform and least square support vector machine improves the peak signal-to-noise ratio (PSNR) of image compression, accelerates the speed of image compression, and obtains better image compression effect.
【作者單位】： 黃淮學(xué)院信息工程學(xué)院;
【基金】：國(guó)家自然科學(xué)基金資助項(xiàng)目(編號(hào):61372058) 遼寧省高等學(xué)校優(yōu)秀人才支持計(jì)劃項(xiàng)目(編號(hào):LR2013012)
【分類號(hào)】：TN911.73
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本文編號(hào)：2523086