| 基于局部插值的双三次图像放大 |
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| 作者姓名： | 纪琳琳 王平 张云峰 |
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| 作者单位： | 湖北工业大学计算机学院,湖北武汉,430068;山东财经大学计算机科学与技术学院,山东济南250014;山东财经大学数字媒体重点实验室,山东济南250014 |
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| 基金项目： | 国家自然科学基金项目(61672018，61772309)；山东省自然科学基金项目(2016GSF120013，2017GGX10109，2018GGX101013)；山东省 省属高校优秀青年人才联合基金项目(ZR2018JL022) |
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| 摘 要： | 以距离和边缘特征为约束，提出构造分片定义的双三次多项式曲面实现图像放大 的新方法，分为构造拟合曲面和修正曲面。以距离和边缘为约束构造对小邻域上像素拟合的二 次多项式采样曲面，所有二次多项式采样曲面加权组合生成分片定义的双三次多项式整体曲面。 由放大图像计算误差图像，由误差图像构造修正曲面的技术，进而提高放大图像精度和视觉效 果。为减少构造二次多项式的计算量，提出对二次多项式系数分类计算算法，能够实现对图像 任意倍数的放大。实验结果表明，该方法不仅提高了放大图像的峰值信噪比(PSNR)、结构相似 度(SSIM)数值精度，也提高了图像的视觉效果。
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| 关 键 词： | 图像放大 二次多项式曲面片 修正曲面 细节和边缘约束 |
Bicubic Image Magnification Based on Local Interpolation |
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| Authors: | JI Lin-lin WANG Ping ZHANG Yun-feng |
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| Affiliation: | 1. School of Computer Science, Hubei University of Technology, Wuhan Hubei 430068, China;2. School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan Shandong 250014, China;3. Shandong Provincial Key Laboratory of Digital Media Technology, Jinan Shandong 250014, China |
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| Abstract: | Image details and edge features play a very important role in the visual effect of images. Therefore, a key to image zooming is to keep image details and edges. In this paper, a new method for image zooming is proposed to construct the sampling surface piecewise defined by bicubic polynomials with the constraints of distance and edge. The method consists of two steps: constructing fitting surface and modifying surface. First, in each neighborhood region where the pixel is located, the new method constructs a quadratic polynomial sampling surface fitting pixels with distance and edge constraints; the weighted combination of all the quadratic polynomial sampling surfaces produces the general surface, which is defined piecewise by the bicubic polynomials. The magnified image obtained from the general surface has higher accuracy and better visual effect. Second, a method for constructing corrected surface is presented, which can improve the quality of the enlarged image. The corrected surface is constructed by the error image that is estimated via magnified image. Moreover, in order to reduce the computational cost of the method, the new method divides the coefficients of the quadratic polynomials into three categories, and proposes an algorithm for calculating each type of coefficients. The proposed method can magnify the image at arbitrary scales. Experimental results show that the new method not only improves the peak signal to noise ratio (PSNR) and structural similarity index (SSIM), but also improves the visual effect of the image. |
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| Keywords: | image magnification quadratic polynomial surface corrected surface detail and edge constraints |
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