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Enhancement method for rendered images of home decoration based on SLIC superpixels

机译：基于slic超像素的家庭装修渲染图像增强方法

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摘要

Rendering technology has been widely used in the home decoration industry in recent years for images of home decoration design. However, due to the fact that rendered images of home decoration design rely heavily on the parameters of Tenderer and the lights of scenes, most rendered images in this industry' require further optimization afterwards. To reduce workload and enhance rendered images automatically, an algorithm utilizing neural networks is proposed in this manuscript. In addition, considering few extreme conditions such as strong sunlight and lights, SLIC superpixels based segmentation is used to choose out these bright areas of an image and enhance them independently. Finally, these chosen areas are merged with the entire image. Experimental results show that the proposed method effectively enhances the rendered images when compared with some existing algorithms. Besides, the proposed strategy is proven to be adaptable especially to those images with obvious bright parts.
机译：近年来，渲染技术已广泛用于家庭装饰行业中的家庭装饰设计图像。但是，由于家庭装饰设计的渲染图像很大程度上依赖于Tenderer的参数和场景的灯光，因此该行业中的大多数渲染图像随后都需要进一步优化。为了减少工作量并自动增强渲染图像，本文提出了一种利用神经网络的算法。此外，考虑到极少的极端条件（例如强烈的阳光和光线），基于SLIC超像素的分割用于选择图像的这些明亮区域并独立增强它们。最后，将这些选择的区域与整个图像合并。实验结果表明，与现有算法相比，该方法有效地增强了渲染图像的质量。此外，所提出的策略被证明特别适用于那些具有明显明亮部分的图像。

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