Frequency-Selective Mesh-to-Grid Resampling for Image Communication
Ján Koloda, Jürgen Seiler, André Kaup · IEEE Transactions on Multimedia · 2017
This paper presents a novel approach for image reconstruction from pixels located at arbitrary noninteger positions, called mesh. This task forms an intrinsic part of various multimedia applications, including superresolution, fisheye imaging, or generations of new views in multicamera systems, among others. We propose a new frequency-selective mesh-to-grid resampling algorithm that aims at producing high quality reconstructions. It is inspired by the existing frequency-selective reconstruction (FSR) algorithm that is known to exhibit high performance when pixels are located on the regular 2D grid. However, if samples that are located at noninteger positions are involved, a severe overfitting problem arises from the fact that nonorthogonal weighted bases sampled at noninteger positions are used for signal modeling. In order to overcome this issue, we propose a novel stabilizing mechanism that is based on a set of adaptively weighted initial estimates, called key points. We also show that Fourier basis, used in the classic grid-based FSR, yields complex signals when noninteger positions are involved. Since digital images are real valued, we propose to employ a 2D cosine transform basis. Experimental results show the superiority of the proposed approach over a wide range of existing reconstruction techniques.