A Comparative Study Of Super-Resolution Interpolation Techniques: Insights For Selecting The Most Appropriate Method

Procedia Computer Science Pub Date : 2024-01-01 DOI:10.1016/j.procs.2024.03.240

Maganti Jahnavi , D. Rajeswara Rao , Amballa Sujatha

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Abstract

Super-resolution interpolation is a popular technique, which is used to increase the image's resolution beyond its original size. However, there are several interpolation techniques available for super-resolution, and determining which technique to use for a given image can be challenging. The aim of the project is to perform a comparative study of different interpolation techniques for super-resolution and identify the best technique for different images. It starts by collecting a dataset of images with different characteristics such as noise, blur, and contrast and then preprocess the images and apply different interpolation techniques such as nearest-neighbor, bilinear, bicubic, Lanczos and Spline etc. The super-resolved images are evaluated and compared using different metrics such as Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Mean Opinion Score (MOS). Based on the results of comparative study, conclusions about the strengths and weaknesses of each method are drawn. And the most appropriate interpolation technique for specific application is identified.

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超分辨率插值技术比较研究：选择最合适方法的启示

超分辨率插值是一种流行的技术，用于提高图像的分辨率，使其超过原始尺寸。然而，有多种插值技术可用于超分辨率，而确定对给定图像使用哪种技术具有挑战性。该项目的目的是对用于超分辨率的不同插值技术进行比较研究，并确定适用于不同图像的最佳技术。项目首先收集具有不同特征（如噪声、模糊和对比度）的图像数据集，然后对图像进行预处理，并应用不同的插值技术，如近邻、双线性、双三次、Lanczos 和 Spline 等。使用不同的指标，如峰值信噪比（PSNR）、结构相似性指数（SSIM）和平均意见分数（MOS），对超分辨图像进行评估和比较。根据比较研究的结果，得出了每种方法的优缺点。并为特定应用确定了最合适的插值技术。

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