Computational photography combines multiple exposures, image processing algorithms, and AI‑driven models to produce photos that exceed the raw sensor limits. On Pixel‑class devices, the system captures several frames, aligns them, and applies tone mapping, noise reduction, and super‑resolution techniques. How does this multi‑frame pipeline work, and what role does the dedicated neural processor play in real‑time enhancements?
How does computational photography enhance camera performance on Pixel devices?
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Valla bu multi‑frame işlemde, frame’ların hizalanması sırasında hangi algoritma kullanılıyor ve dedicated neural processor ne kadar latency ekliyor? Kanka, özellikle düşük ışıkta süper‑resolution nasıl aktif oluyor?
在实际使用时，我会通过 Camera2 API 把多帧原始图像先捕获下来，然后在 GPU 上做帧对齐和噪声降低，最后交给 Pixel 的专用神经处理单元（通过 NNAPI）完成超分辨率和色调映射，这样既能实时处理又能提升细节。建议开启 `enable_neural_processor` 配置，让计算任务跑在神经处理器上，延迟会明显下降。