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Evaluation of 360° Image Projection Formats; Comparing Format Conversion Distortion Using Objective Quality Metrics.

Ikram Hussain¹, Oh-Jin Kwon¹

¹Department of Electrical Engineering, Sejong University, 209 Neungdong-ro, Seoul 05006, Korea.

Journal of Imaging

|August 30, 2021

Summary

This summary is machine-generated.

This study evaluates 360° image projection formats, comparing distortion levels during conversions. The hybrid equi-angular cube-map format is identified as the best solution for frequently converted 360° images.

Keywords:

360° image cube-map projection cylindrical projection equal-area projection equi-rectangular projection image quality evaluation objective image quality metric

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Area of Science:

Computer Vision
Image Processing
Multimedia Technology

Background:

360° cameras capture spherical images mapped to 2D planes using various projection formats.
Limited standards exist for assessing the quality of 360° images.
Distortion during projection format conversion is a significant challenge.

Purpose of the Study:

To compare various 360° image projection formats.
To evaluate distortion caused by mapping operations.
To identify the most suitable format for 360° image services requiring frequent conversions.

Main Methods:

Evaluated projection formats: equi-rectangular, equal-area, cylindrical, cube-map, and modified versions.
Assessed performance based on minimizing distortion during format conversion.
Used objective quality metrics on sample images selected for perceptual quality attributes.

Main Results:

The hybrid equi-angular cube-map format demonstrated the least distortion.
This format is identified as the most appropriate for 360° image services with frequent format conversions.
A ranking of projection formats based on distortion is presented.

Conclusions:

The hybrid equi-angular cube-map format is recommended for future 360° image standards.
Objective quality metrics are effective for evaluating 360° image projection formats.
Further research can build upon the format ranking for optimal 360° image representation.