针对电影级高分辨率文件，实现智能压缩保画质。
Adaptive Iterative Compression for High-Resolution Files: an Approach Focused on Preserving Visual Quality in Cinematic Workflows
- 动态调整压缩参数，基于SSIM和PSNR反馈优化
- 最高省83.4%存储，保持SSIM>0.95的视觉保真度
- 适合专业影视、医疗影像等对画质要求高的场景
本研究提出一种用于电影制作与数字保存中高分辨率DPX导出TIFF文件的自适应迭代压缩模型。该模型通过SSIM与PSNR指标动态调节三种配置（C0、C1、C2）的压缩参数，在实现最高83.4%存储缩减的同时，维持高视觉保真度（SSIM > 0.95）。在黑白经典、柔色调剧情片与复杂动作片三类不同影片上的验证表明，该方法能有效保留关键视觉元素，显著降低存储需求。专业评审对最优配置C1的接受率达90%，关键区域伪影低于人眼感知阈值。与JPEG2000和H.265对比显示，在同等压缩率下，本方法在高比特深度内容上表现出更优的质量保持能力。尽管需额外计算开销，其存储优势与质量控制能力使其适用于专业工作流，并有望推广至医学影像与云存储优化领域。
原文摘要 · Abstract (English)
This study presents an iterative adaptive compression model for high-resolution DPX-derived TIFF files used in cinematographic workflows and digital preservation. The model employs SSIM and PSNR metrics to dynamically adjust compression parameters across three configurations (C0, C1, C2), achieving storage reductions up to 83.4 % while maintaining high visual fidelity (SSIM > 0.95). Validation across three diverse productions - black and white classic, soft-palette drama, and complex action film - demonstrated the method's effectiveness in preserving critical visual elements while significantly reducing storage requirements. Professional evaluators reported 90% acceptance rate for the optimal C1 configuration, with artifacts remaining below perceptual threshold in critical areas. Comparative analysis with JPEG2000 and H.265 showed superior quality preservation at equivalent compression rates, particularly for high bit-depth content. While requiring additional computational overhead, the method's storage benefits and quality control capabilities make it suitable for professional workflows, with potential applications in medical imaging and cloud storage optimization.
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