一个智能无线通道使用基于对称卷积的启发式辅助剩余注意网络损坏了图像消噪框架
Sreedhar Mala1, Aparna Kukunuri2
1ECE, Jawaharlal Nehru Technological University Anantapur, Anantapur, Andhra Pradesh, India.
概括
本研究介绍了一种使用自适应升起波纹转换和基于对称卷积的剩余注意力网络的先进图像否定方法. 这种方法显著提高了无线通道噪声损坏的图像质量.
科学领域:
- 信号处理 信号处理
- 图像处理 图像处理
- 计算机视觉 计算机视觉
背景情况:
- 无线图像传输容易产生噪音,降低图像质量并阻碍信息提取.
- 有效的图像无色化对于准确分析和纠正损坏图像中的错误至关重要.
研究的目的:
- 为在无线传输过程中损坏的图像开发一种高效的图像消除方法.
- 为了纠正错误并减轻频道退化对图像质量的影响.
主要方法:
- 图像使用自适应式升起波形变换 (ALWT) 进行分解.
- 基于对称卷积的剩余注意网络 (SC-RAN) 用于剩余图像提取.
- 参数通过混合能源金甲虫虫优化器 (HEGTBO) 进行优化.
主要成果:
- 开发的模型实现了 31.69% 的峰值信号噪声比率 (PSNR).
- 拟议的方法在消除损坏的图像方面取得了显著的改进.
结论:
- ALWT,SC-RAN和HEGTBO的综合方法有效地提高了图像质量.
- 这项研究提供了一个强大的解决方案,用于无线通信环境中的图像无声化.
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