Publication Date
Spring 2023
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Electrical Engineering
Advisor
Chang Choo
Subject Areas
Electrical engineering
Abstract
In this thesis, an image interpolation scheme using an adaptive windowed sinc, which varies in length and frequency response guided by the Laplacian operator, is proposed to improve quality and accuracy. First, an optimization is performed to minimize the squared error for each sliding window by sweeping a range of windowed sinc filters with varying filter lengths. The relationship between the windows, filter length, and edge intensity is analyzed to determine the optimal beta value and filter length. This analysis inspires an image interpolation approach that uses the Laplacian of each sliding window to choose the optimal beta and filter length. The performance of the proposed approach is compared with the optimized result, as well as traditional interpolation methods such as bilinear and bicubic, in terms of PSNR, SSIM, and a subjective visual test. The findings demonstrate the effectiveness of the proposed method in enhancing the resolution of images, contributing to a deeper understanding of adaptive windowed sinc filters and their potential applications in image interpolation.
Recommended Citation
Nguyen, Dang, "Adaptive Windowed Sinc Filter for Image Interpolation" (2023). Master's Theses. 5412.
DOI: https://doi.org/10.31979/etd.cqpm-99c3
https://scholarworks.sjsu.edu/etd_theses/5412