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

机译：基于Slic Superpixels的家居装饰呈现的增强方法

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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 renderer 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：近年来家居装饰设计的图像已广泛应用于家居装饰行业。然而，由于家庭装饰设计的图像依赖于渲染器的参数和场景的灯光的渲染图像，在该行业中大多数渲染图像之后需要进一步优化。为了减少工作量和增强渲染图像自动，在此稿件中提出了一种利用神经网络的算法。此外，考虑到很少的极端条件，如强大的阳光和灯光，基于SLIC Superpixels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，这些所选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呈现的图像。此外，拟议的策略被证明是适应性的，特别是那些具有明显亮点的那些形象。

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