Edge Curve Scaling and Smoothing with Cubic Spline Interpolation for Image Up-Scaling

• Main Authors: Wei-Chen Wu, 吳維宸
• Other Authors: Chiu, Ching-Te
• Format: Others
• Language: en_US
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/00072826594831767376

碩士 === 國立清華大學 === 資訊工程學系 === 101 === Image up-scaling is an important technique to increase the resolution of an image. While earlier interpolation based approaches such as the bilinear and the bicubic method cause blurring and ringing artifacts in edge regions of the up-scaled image due to the loss of high frequency details. Recent approaches such as the local-self example super resolution can achieve very promising up-scaling results while their computation cost are high because they recover high frequency components of the whole image. In this paper, we proposed an image up-scaling method via an up-scaled edge map. By predicting edge regions of the up-scaled image, we recover high frequency components of edge regions of the up-scaled image to improve the sharpness and reduce ringing artifacts. We propose an edge curve scaling method with cubic spline interpolation to up-scale an edge map. If an edge curve is directly applied to the cubic spline interpolation function for edge curve up-scaling , the edge curve scaling results have zigzag artifacts. We also propose a simple smoothing function to avoid the zigzag problems and maintain the contour shape of images. Our methods can reduce execution time by 90% because we only perform high frequency components recovery on edge regions while other methods adopt to recover the high frequency components of every points in the up-scaled image. Experimental results show that we can achieve similar performances with the local self example super resolution method.