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AN IMAGE SEGMENTATION METHOD FOR FUNCTION APPROXIMATION OF GRADATION IMAGES

机译:渐近图像功能逼近的图像分割方法

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Function-approximated images are useful for quality-maintained affine-transform. However, it is difficult for conventional approximation methods to accurately function-approximate images including numerous small color regions such as gradations, because no appropriate segmentation is performed. We propose a new image segmentation method for function-approximation of gradation images and its description format. In this method, a gradation pattern in a image is recognized as a region by a new labeling method using multiple regression analysis of 2-variable functions. Pixel values in segmented color regions can be reproduced by using the contour and region approximation. The experiments show that in this method we can reduce the processing time and the file size becomes compact. By evaluating approximation accuracy by PSNR, it is proved that our approach improves the drawing accuracy.
机译:函数逼近图像对于质量保持仿射变换很有用。但是,对于传统的逼近方法,由于没有执行适当的分割,因此难以对包括许多小的色彩区域(例如,灰度级)的图像进行精确的功能逼近。针对灰度图像的函数逼近及其描述格式,提出了一种新的图像分割方法。在该方法中,通过使用2-变量函数的多元回归分析的新标记方法,将图像中的灰度图案识别为区域。可以通过使用轮廓和区域近似来再现分段颜色区域中的像素值。实验表明,采用这种方法可以减少处理时间,并且文件大小变得紧凑。通过用PSNR评估近似精度,证明了我们的方法提高了绘图精度。

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