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Generation of all-focus images and depth-adjustable images based on pixel blurriness

机译:基于像素模糊度生成全焦点图像和深度可调图像

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Taking a picture containing all-focus objects with regardless of distance is difficult. A feasible strategy to generate an all-focus image relies on multiple images with different focus settings. Furthermore, image refocusing with side information is applied to all-focus image to generate depth-adjustable image which is like to real-world photos at the specified depth-of-field. In this paper, we propose image fusion and refocusing methods for generation of all-focus image and depth-adjustable image. During fusion procedure, measuring pixels' blurriness of multi-focus reference images is the first process. Then, all-focus image composed of sharpest pixels among reference images, index map, and standard deviation-index table are yielded. The objective of standard deviation-index table is to connect relationship between Gaussian lowpass filter and index. During refocusing procedure, different Gaussian lowpass filters applied to all-focus image by referring to index map and standard deviation-index table, and then depth-adjustable image is generated. The experiment results demonstrate the proposed methods are better than the compared approaches in computational complexity and quality of all-focus image and depth-adjustable image.
机译:拍摄距离不限的全焦点物体的照片很困难。生成全焦点图像的可行策略依赖于具有不同焦点设置的多幅图像。此外,将带有辅助信息的图像重新聚焦应用于全焦点图像,以生成深度可调的图像,该图像类似于在指定景深处的真实照片。在本文中,我们提出了用于产生全焦点图像和深度可调图像的图像融合和重新聚焦方法。在融合过程中,测量多焦点参考图像的像素模糊度是第一步。然后,产生由参考图像中最清晰的像素组成的全焦点图像,索引图和标准偏差-索引表。标准偏差指标表的目的是连接高斯低通滤波器和指标之间的关系。在重新聚焦过程中,通过参考索引图和标准偏差-索引表将不同的高斯低通滤波器应用于全聚焦图像,然后生成深度可调节的图像。实验结果表明,所提出的方法在全焦点图像和深度可调图像的计算复杂度和质量上均优于比较方法。

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