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Study on the application of embedded zero-tree wavelet algorithm in still images compression

机译:嵌入式零树小波算法在静止图像压缩中的应用研究

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An image has directional selection capability with high frequency through wavelet transformation. It is coincident with the visual characteristics of human eyes. The most important visual characteristic in human eyes is the visual covering effect. The embedded Zero-tree Wavelet (EZW) coding method completes the same level coding for a whole image. In an image, important regions (regions of interest) and background regions (indifference regions) are coded through the same levels. On the basis of studying the human visual characteristics, that is, the visual covering effect, this paper employs an image-compressing method with regions of interest, i.e., an algorithm of Embedded Zero-tree Wavelet with Regions of Interest (EZWROI Algorism) to encode the regions of interest and regions of non-interest separately. In this way, the lost important information in the image is much less. It makes full use of channel resource and memory space, and improves the image quality in the regions of interest. Experimental study showed that a resumed image using an EZW_ROI algorithm is better in visual effects than that of EZW on condition of high compression ratio.
机译:通过小波变换,图像具有高频的方向选择能力。它与人眼的视觉特征相吻合。人眼最重要的视觉特征是视觉遮盖效果。嵌入式零树小波(EZW)编码方法完成了整个图像的相同级别编码。在图像中,重要区域(关注区域)和背景区域(区别区域)通过相同级别进行编码。在研究人类视觉特征即视觉覆盖效果的基础上,采用感兴趣区域的图像压缩方法,即具有感兴趣区域的嵌入式零树小波算法(EZWROI Algorism)分别对感兴趣的区域和不感兴趣的区域进行编码。这样,图像中丢失的重要信息就少得多。它充分利用了通道资源和存储空间,并提高了感兴趣区域中的图像质量。实验研究表明,在高压缩比的情况下,使用EZW_ROI算法的恢复图像在视觉效果上优于EZW。

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