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Geometry-Aware Transform Pruning for Omnidirectional Image Compression

delete2026-08-24
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OA
AI
T
Thiago L. T. da Silveira
E
Enzo B. Segala
F
Fábio M. Bayer
R
Renato J. Cintra
DOI:10.1109/access.2026.3726449delete
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Abstract

Abstract

En 中文
This study introduces a latitude-adaptive discrete cosine transform pruning method designed for low-complexity omnidirectional image compression. The proposed approach exploits the Nyquist-Shannon sampling theorem together with the geometric characteristics of the de facto sphere-to-plane mapping for omnidirectional media—the equirectangular projection—to selectively apply pruned transforms in block-based codecs. By adapting the transform support according to the spatial redundancy introduced by equirectangular sampling distortions, the method reduces unnecessary transform coefficients while preserving the relevant visual information. The proposed framework decreases the arithmetic complexity of both the transform and quantization stages, achieving substantial reductions in the number of additions and multiplications compared with the conventional JPEG pipeline. Experimental results on benchmark high-resolution omnidirectional images demonstrate that the proposed solution attains compression efficiency comparable to that of state-of-the-art low-complexity block-based techniques in terms of bitrate and image quality. These results highlight the potential of the proposed framework for resource-constrained transform-based omnidirectional image codecs.
Keywords:
Data compression
digital signal processing
image coding
image processing
image quality
image reconstruction
image representation
multimedia communication
multimedia systems
transform coding

Journal

IEEE Access cover
IEEE Access
IF:
3.6
Papers:
9.8W
Citations:
29.4W

Organization

U
Universidade Federal de Pernambuco
Scholars:
1.3W
Papers: 7.3K
Citations: 5.3K
F
federal university of rio grande do sul
Scholars:
1.0K
Papers: 423
Citations: 0
Universidade Federal de Santa Maria cover
Universidade Federal de Santa Maria
Scholars:
380
Papers: 127
Citations: 5.4K
F
federal university of santa maria
Scholars:
703
Papers: 223
Citations: 0
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