图像中较暗部分增强的非参数方法

Sachin Gavhane, Amruta Pokhare, S. Shitole
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引用次数: 0

摘要

在较暗区域捕获的图像在处理和删除重要数据时增加了复杂性。这些图片的改进鼓励我们恢复重要的信息。采用基于人工神经网络的误差反向传播(BP)算法增强图像的阴影区域。本文使用的数据集是带有增强输出(对数变换)的阴影图像,因此模型将能够学习增强任意给定图像的阴影区域。在得到的结果中成功地减少了图像中的较暗区域。仍然存在通过调整和变化到提出的非参数方法的各种参数的改进范围。
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Non-Parametric Method for Enhancement of Darker Portion in an Image
Images caught in darker area builds complexities in handling and removing essential data. Improvement of such pictures encourages us to recover significant information. ANN based error back propagation (BP) algorithm is used for enhancing shadow region of an image. Dataset used in this paper is a shadow image with its enhanced output (log transformed), so that model will be able to learn to enhance the shadow region of any given image. Darker locale in an image are successfully reduced in the results obtained. Still there is a scope of improvement through adjustments and variations into various parameters of proposed non-parametric approach.
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