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Image Quality Evaluation of Light Field Image Based on Macro-Pixels and Focus Stack.

Chunli Meng1, Ping An1, Xinpeng Huang1

  • 1Key Laboratory for Advanced Display and System Application, Shanghai Institute for Advanced Communication and Data Science, School of Communication and Information Engineering, Shanghai University, Shanghai, China.

Frontiers in Computational Neuroscience
|February 7, 2022
PubMed
Summary

This study introduces MPFS, a novel light field (LF) image quality evaluation model. It accurately assesses global and local angular-spatial distortions for precise LF image quality assessment.

Keywords:
cornerfocus stacklight fieldmacro-pixelsobjective image quality assessment

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Area of Science:

  • Computer Vision
  • Image Processing
  • Signal Processing

Background:

  • Light field (LF) images possess a complex angular-spatial structure, presenting unique challenges in image processing compared to traditional 2D images.
  • Loss of angular-spatial structure in LF images is a critical indicator of distortion, necessitating specialized feature extraction methods for accurate analysis.

Purpose of the Study:

  • To propose a novel light field image quality evaluation model (MPFS) that addresses the complexities of angular-spatial structure loss.
  • To develop a method for predicting global angular-spatial distortion and evaluating local angular-spatial quality in distorted LF images.

Main Methods:

  • Angular distortion is evaluated using macro-pixel luminance and chrominance, with spatial texture saliency used for global distortion prediction.
  • Local angular-spatial quality is analyzed via principal components of the focus stack, assessing focalizing structure damage using corner and texture features.
  • A combined approach integrating global and local evaluation models is employed for comprehensive LF image quality assessment.

Main Results:

  • The proposed MPFS model effectively predicts global angular-spatial distortion by analyzing macro-pixel characteristics and spatial texture.
  • Local quality assessment accurately quantifies focalizing structure damage using focus stack principal components and structural features.
  • Extensive experiments demonstrate the high efficiency and precision of the MPFS model in evaluating overall LF image quality.

Conclusions:

  • The MPFS model provides a robust framework for evaluating light field image quality by considering both global and local angular-spatial distortions.
  • The method's ability to analyze complex LF image structures offers significant advancements in image quality assessment.
  • The proposed approach achieves high efficiency and precision, outperforming existing methods in LF image quality evaluation.