保持轮廓清晰光滑的灰度图像放大算法

灰度图像放大时，插值所具有的平滑作用会退化图像的高频部分，使放大图像轮廓变得模糊，文中提出一种基于拟合分界线的插值放大算法，该处包括分割和插值放大两个步骤；分割是搜索出灰度图像的突变象素点，并用三次均匀B样条把它们拟合为光滑分界线，以把整幅图像分割为若干子区域；插值放大是基于拟合分界线对图像插值，即插值操作限定于原图像的某一子区域内进行。采用文中算法得到的放大图像不仅可保持轮廓清晰，而且可持续轮廓光滑，最后给出三个放大实例，证明了 文中放大算法比常规算法产生的图像质量高。

Gray Image Magnification with Reserved Sharp and Smooth Contour

When gray images are magnified, the smoothing effect of gray level interpolation may degrade the fine details in images and make contours become blurred. An interpolation magnification algorithm for gray images based on the fitted dividing curves is presented. This algorithm includes two stages: segmentation and interpolation magnification. In the segmentation stage, the abrupt transition pixels in the image are extracted and fitted as cubic uniform B\|spline. This process results in fitted dividing curves and is used to divide the whole image into several subimages. In interpolation magnification stage, the interpolation operation is limited to inside a subimage. This magnification operation eliminates the common zigzag and blurred effect occurred in conventional magnified images and keeps the contours of magnified image still sharp and smooth.