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Image Thumbnails That Represent Blur and Noise

机译:代表模糊和噪点的图像缩略图

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摘要

The information about the blur and noise of an original image is lost when a standard image thumbnail is generated by filtering and subsampling. Image browsing becomes difficult since the standard thumbnails do not distinguish between high-quality and low-quality originals. In this paper, an efficient algorithm with a blur-generating component and a noise-generating component preserves the local blur and the noise of the originals. The local blur is rapidly estimated using a scale-space expansion of the standard thumbnail and subsequently used to apply a space-varying blur to the thumbnail. The noise is estimated and rendered by using multirate signal transformations that allow most of the processing to occur at the lower spatial sampling rate of the thumbnail. The new thumbnails provide a quick, natural way for users to identify images of good quality. A subjective evaluation shows the new thumbnails are more representative of their originals for blurry images. The noise generating component improves the results for noisy images, but degrades the results for textured images. The blur generating component of the new thumbnails may always be used to advantage. The decision to use the noise generating component of the new thumbnails should be based on testing with the particular image mix expected for the application.
机译:通过过滤和二次采样生成标准图像缩略图时,有关原始图像模糊和噪点的信息会丢失。由于标准缩略图无法区分高质量原稿和低质量原稿,因此图像浏览变得困难。在本文中,具有模糊产生分量和噪声产生分量的有效算法保留了局部模糊和原稿的噪声。使用标准缩略图的比例空间扩展可以快速估计局部模糊,然后将局部变化的模糊应用于缩略图。噪声是通过使用多速率信号转换来估计和渲染的,该转换允许大多数处理以缩略图的较低空间采样率发生。新的缩略图为用户提供了一种快速自然的方式来识别高质量的图像。主观评估显示,新缩略图更能代表模糊图像的原始缩略图。噪声生成组件可改善嘈杂图像的结果,但会降低纹理图像的结果。可以总是使用新缩略图的模糊生成组件。使用新缩略图的噪声生成组件的决定应基于对应用程序预期的特定图像混合的测试。

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