Abstract
Image interpolation is important in image zooming. To improve the quality of image zooming, in this work, we proposed a class of rational quadratic trigonometric Hermite functions with two shape parameters and two classes of C 1 -continuous Coons patches constructions over a triangular domain by improved side–side method and side–vertex method. Altering the values of shape parameters can adjust the interior shape of the triangular Coons patch without influencing the function values and partial derivatives of the boundaries. In order to deal with the problem of well-posedness in image zooming, we discussed symmetrical sufficient conditions for region control of shape parameters in the improved side–side method and side–vertex method. Some examples demonstrate the proposed methods are effective in surface design and digital image zooming. C 1 -continuous Coons patches constructed by the proposed methods can interpolate to scattered 3D data. By up-sampling to the constructed interpolation surface, high-resolution images can be obtained. Image zooming experiment and analysis show that compared to bilinear, bicubic, iterative curvature-based interpolation (ICBI), novel edge orientation adaptive interpolation scheme for resolution enhancement of still images (NEDI), super-resolution using iterative Wiener filter based on nonlocal means (SR-NLM) and rational ball cubic B-spline (RBC), the proposed method can improve peak signal to noise ratio (PSNR) and structural similarity index (SSIM). Edge detection using Prewitt operator shows that the proposed method can better preserve sharp edges and textures in image zooming. The proposed methods can also improve the visual effect of the image, therefore it is efficient in computation for image zooming.
Highlights
Image zooming refers to constructing a high resolution (HR) image from a low resolution (LR)image, which is to estimate unknown pixels from known pixels in essence
Image zooming experiment and analysis show that compared to bilinear, bicubic, iterative curvature-based interpolation (ICBI), novel edge orientation adaptive interpolation scheme for resolution enhancement of still images (NEDI), super-resolution using iterative Wiener filter based on nonlocal means (SR-NLM) and rational ball cubic B-spline (RBC), the proposed method can improve peak signal to noise ratio (PSNR) and structural similarity index (SSIM)
Some experiments on image zooming show that compared to bilinear, bicubic, iterative curvature-based interpolation (ICBI) [22], novel edge orientation adaptive interpolation scheme for resolution enhancement of still images (NEDI) [23], super-resolution using iterative Wiener filter based on nonlocal means (SR-NLM) [24] and rational ball cubic B-spline (RBC) [25], the proposed methods can improve the peak signal to noise ratio (PSNR) and structural similarity index (SSIM)
Summary
Image zooming refers to constructing a high resolution (HR) image from a low resolution (LR)image, which is to estimate unknown pixels from known pixels in essence. Image interpolation technology can preserve rich texture information and sharp edges under certain conditions. Image interpolation technology plays an important role in the field of image processing and is widely used in various fields, such as aerospace, military, communications, remote sensing satellites, television and film production. The earliest interpolation methods consist of nearest-neighbor interpolation, bilinear interpolation [1], bicubic interpolation [2,3] and so on. These methods work well in smooth areas, with obvious alias and ringing in edge texture areas. Muresan et al [5] proposed a novel interpolation method based on optimal recovery and adaptively determining the quadratic signal class from the local image
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call