基于显著特征和线性回归预测的渐进图像传输

Chinchen Chang, J. Chuang
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引用次数: 1

摘要

渐进图像传输常用于低带宽通信或有限带宽环境中。当用户在网站上浏览图像时,网络服务器首先向接收者发送低质量的图像,然后通过随后的传输逐渐提高图像质量。由于图像尺寸越来越大,因此必须开发一种灵活有效的技术来帮助用户快速浏览或检索网站上的图像。为此,本文提出了利用显著特征和预测技术进行渐进图像传输。在我们的方法中,首先需要提取图像的重要特征。接下来,这些特征根据它们的优先级被发送给接收者。为了降低传输数据的编码成本,提出了采样、量化和线性回归预测三种方法。
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Progressive Image Transmission Using Significant Features and Linear Regression Prediction
Progressive image transmission is often used in low bandwidth communications or in limited bandwidth environments. When a user browses an image on a website, the web server first sends a low quality image to the receiver and then gradually improves the image quality by subsequent transmissions .Because the image size becomes larger and larger, it is essential to develop a flexible and efficient technique to help users quickly browse or retrieve images on a website. For this reason, using significant features along with a prediction technique for progressive image transmission is proposed in this paper. In our method, significant features of an image need to be extracted first. Next, these features, according to their priority, are sent to the receiver. For reducing the encoding cost of the transmitted data, three approaches, sampling, quantization, and linear regression prediction, are also presented.
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