Open AccessTesting of Image Resolution Enhancement Techniques Using Bi-cubic Spatial Domain Interpolation
Author(s) -
M. Arief Bustomi
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1417/1/012028
Subject(s) - interpolation (computer graphics) , pixel , image resolution , bicubic interpolation , image scaling , mathematics , sub pixel resolution , computer vision , artificial intelligence , spline interpolation , image (mathematics) , algorithm , image processing , computer science , digital image processing , bilinear interpolation
The technique for increasing digital image resolution from low-resolution image to high-resolution image based on digital image processing is called the super-resolution technique. In this paper, a super-resolution technique is presented using a two-dimensional bi-cubic interpolation method in the spatial domain. The order of the super resolution method applied is as follows: (1) selecting ten images as samples, (2) decrease the sample image resolution to one-fourth of the original resolution by deleting three quarters of the pixel number, (3) increasing the image resolution of a quarter of the part becomes like the initial resolution using bi-cubic interpolation for three quarters of the additional new pixels, (4) testing this bi-cubic interpolated image with the same pixel-sized initial image, (5) using parameters: average value, minimum value, maximum value and standard deviation value as a comparison parameter between bi-cubic interpolated images and the same pixel-sized initial image. The results obtained from the super-resolution technique using spatial bi-cubic interpolation are: (1) The average error value of the bi-cubic interpolation method in image objects in this study is between 4% to 10% or still quite low, (2) Bi-cubic interpolation methods can work well on square pixel-sized images (m = n) compared to non-square pixel-sized images, (3) Bi-cubic interpolation turns out to produce an array of image pixel values that mirror symmetry against the main diagonal lines of the image before being interpolated.