CAJ | 학술논문

该文提出一种基于结构成分双向扩散的插值方法，有效地减小了插值图像的边缘扩散，从而获得更为清晰的边缘。该方法采用改进的耦合双向扩散滤波器对轮廓模板插值图像进行边缘增强。其中，为了使滤波器更精确地作用于边缘轮廓，利用形态成分分析(MCA)分离出初始插值图像中的结构分量再实行滤波；同时，改进双向扩散模型，使其能够根据边缘梯度自适应地调整边缘扩散程度，且更加柔和地控制梯度方向的像素值变化。实验结果表明，对比传统的插值方法、相关的边缘自适应插值方法以及几种应用普遍的商用软件，该方法获得的插值图像主、客观质量均有明显提升，不仅有效提高图像锐度，且边缘光滑、过渡自然，避免产生边缘锯齿和过度的人工效应。
해문제출일충기우결구성분쌍향확산적삽치방법，유효지감소료삽치도상적변연확산，종이획득경위청석적변연。해방법채용개진적우합쌍향확산려파기대륜곽모판삽치도상진행변연증강。기중，위료사려파기경정학지작용우변연륜곽，이용형태성분분석(MCA)분리출초시삽치도상중적결구분량재실행려파；동시，개진쌍향확산모형，사기능구근거변연제도자괄응지조정변연확산정도，차경가유화지공제제도방향적상소치변화。실험결과표명，대비전통적삽치방법、상관적변연자괄응삽치방법이급궤충응용보편적상용연건，해방법획득적삽치도상주、객관질량균유명현제승，불부유효제고도상예도，차변연광활、과도자연，피면산생변연거치화과도적인공효응。
An image interpolation method based on structure component bidirectional diffusion is proposed in this paper, by which the edge diffusion in image magnification is effectively decreased and the sharpening edges are generated. In this method, the edges are enhanced by using the advanced coupling of bidirectional diffusion filter after contour stencils interpolation. In order to deal with the edge contours more precisely, the structure component of initial interpolated image is filtered after separating from the initial interpolated image via Morphological Component Analysis (MCA). Furthermore, the coupling of bidirectional filter is improved to adaptively adjust the edge diffusion degree according to the edge gradient, and to control pixels value change along gradient direction more gently. The experimental results show that, the proposed method outperforms other comparing algorithms including the traditional interpolation algorithm and the related edge adaptive interpolation algorithms and several widely-used commercial software in terms of both objective and visual quality of the interpolation image. The method enhances the image sharpness effectively, and gains smooth edges, nature transition, also avoids producing the edge aliasing and overshoot artifacts.