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首页> 外文会议>International Joint Conference on Computer Science and Software Engineering >Modified Scale-Space Analysis in Frequency Domain Based on Adaptive Multiscale Gaussian Filter for Saliency Detection
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Modified Scale-Space Analysis in Frequency Domain Based on Adaptive Multiscale Gaussian Filter for Saliency Detection

机译：基于自适应多尺度高斯滤波器的显着性频域尺度空间分析

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摘要

The salient region is an area in the image that is paid attention from a human. It is a distinctive feature from neighbors such as color, shape or pattern. Saliency detection is a model that imitates the human visual system to perceive the scene. It has been widely used in many vision systems. Many papers use the smoothing or suppressing technique to extract a desirable output as so-called saliency map. Even though most of these researches achieve saliency detection based on the filter, the size of the filter is fixed. This leads to a filter ineffective when applying to the whole area of each image. In order to solve this issue, an adaptive multiscale Gaussian filter (MSS) for scale-space analysis in the frequency domain is proposed. The proposed filter is extended from an adaptive median filter which is a powerful method to remove the noise from the input image. This paper proposes the method that offers the appropriate filter to suppress the repeated pattern spectrum of each region in each image before extracting the saliency map. The experimental result shows that the proposed method outperforms the baseline methods, which includes HFT, Itti, SAL, SR and SUN.
机译：显着区域是图像中人类关注的区域。这是邻居与众不同的特征，例如颜色，形状或图案。显着性检测是模仿人类视觉系统感知场景的模型。它已被广泛用于许多视觉系统。许多论文使用平滑或抑制技术来提取所需的输出，即所谓的显着图。尽管大多数这些研究都基于过滤器实现了显着性检测，但过滤器的大小是固定的。当应用于每个图像的整个区域时，这会导致滤镜无效。为了解决这个问题，提出了一种用于频域尺度空间分析的自适应多尺度高斯滤波器（MSS）。所提出的滤波器是从自适应中值滤波器扩展而来的，这是一种从输入图像中去除噪声的强大方法。本文提出了一种在提取显着图之前，提供适当的滤波器来抑制每个图像中每个区域的重复图案谱的方法。实验结果表明，该方法优于HFT，Itti，SAL，SR和SUN等基线方法。

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