Work

A method for retinal inspired foveated image reconstruction

Year: 2025

Type: article

Abstract: The foveal mechanism of the human retina produces sharp central vision with a blurred periphery. By generating foveated images that more closely replicate this mechanism, it is possible to significantly enhance immersion and deliver a more natural visual experience in virtual environments and related applications. In this paper, we proposed a two-stage foveated image reconstruction method to simulate a biologically plausible foveated retina. In the first stage, a monocular humanoid field of view (FOV) model is designed based on the mapping relationship between the human retina and the camera sensor, enabling the capture of images with a human-like FOV using a commonly available uniform-pixel camera. During the second stage, a non-uniform pixel sampling approach is presented to approximate the spatial distribution of photoreceptors across the retina, combined with biharmonic spline-based interpolation for natural-looking resampling. Qualitative and quantitative results demonstrate that the foveated images generated by the proposed method exhibit better consistency with human visual perception than existing representative methods.

Source: Signal Processing

DOI: 10.1016/j.sigpro.2025.110459

Authors: Haoming Xiang, Xiaohua Xia, Haiyun Tan, Zhiwei Duan

Institution: Chang'an University

Language: English

Topic: Advanced Vision and Imaging

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,190

Funders: National Natural Science Foundation of China, Department of Transportation of Sichuan Province, Key Research and Development Projects of Shaanxi Province