單元 13 · 雜訊與降噪

python3 - <<'EOF'
import rawpy, numpy as np, subprocess
for g in [1, 2, 4, 8]:
    subprocess.run(['rpicam-still','--raw','--gain',str(g),
                    '--shutter','20000','-o',f'g{g}.dng'])
    raw = rawpy.imread(f'g{g}.dng').raw_image
    roi = raw[500:1500,500:1500].astype(float)
    print(f'gain={g}  mean={roi.mean():.1f}  std={roi.std():.1f}')
EOF

{ "Denoise": { "strength": 0.3 } }

python3 - <<'EOF'
import rawpy, numpy as np
raw = rawpy.imread('black.dng').raw_image
hot = raw > raw.mean() + 10 * raw.std()
print('hot pixel 數量:', hot.sum())
print('最亮:', raw.max())
EOF

# 假設：目標 SNR >= 30dB（σ/S 比值 < 3.2%）
# 量測：gain=8 時 σ=20, 訊號=400
SNR = 20 * log10(400/20) = 26 dB   # 低於目標

# 選項 A：曝光加倍（真實訊號）→ 訊號 800, σ≈28 → SNR 29 dB
# 選項 B：改回 gain=4（σ 較小）但補光 → 訊號 800, σ≈18 → SNR 33 dB ✓
# 結論：補光 + 降增益 優於 硬拉增益

python3 - <<'EOF'
import rawpy, numpy as np
for name in ['before.dng','after.dng']:
    raw = rawpy.imread(name).raw_image
    hot = (raw > raw.mean() + 10*raw.std()).sum()
    print(name, 'hot pixels:', hot, 'max:', raw.max())
EOF

python3 - <<'EOF'
import rawpy, numpy as np
for ms in [1000, 5000, 20000]:
    raw = rawpy.imread(f'black_{ms}.dng').raw_image
    print(f'曝光{ms}µs: 黑位均值={raw.mean():.1f}')
    # 均值隨曝光線性增 → slope 即 dark current
EOF

#!/bin/bash
# 完全遮光 + 短曝光（最小化 dark current）
# 短曝光讓 dark current 影響最小，量到的是純 read noise
for GAIN in 1 2 4 8; do
  rpicam-still --raw --gain $GAIN --shutter 1000 \
    --awb off --awbgains 1,1 -o rn_g${GAIN}.dng 2>/dev/null
done

python3 - <<'EOF'
import rawpy, numpy as np
print("gain | read_noise(e-) | dark_current_offset")
print("-----|---------------|-------------------")
for g in [1,2,4,8]:
    raw = rawpy.imread(f'rn_g{g}.dng').raw_image.astype(float)
    roi = raw[600:1400, 600:1400]
    std = roi.std()
    mean = roi.mean()
    # 假設 10-bit ADC, 1 LSB ≈ 1 e- (簡化)
    print(f"  {g}  |     {std:5.1f}     |       {mean:.1f}")
    
    # 量測不同區域的雜訊一致性
    zones = {
        'top-left':     raw[100:500, 100:500].std(),
        'center':       roi.std(),
        'bottom-right': raw[1500:1900, 2100:2500].std()
    }
    for zone, s in zones.items():
        print(f"    {zone}: σ={s:.1f}")
EOF

#!/bin/bash
# 1. read noise：遮光 + 短曝光（1ms）不同增益
for G in 1 2 4 8 16; do
  rpicam-still --raw --gain $G --shutter 1000 \
    --awb off --awbgains 1,1 -o rn_g$G.dng 2>/dev/null
done

# 2. dark current：遮光 + 長曝光不同時長
for T in 1000 10000 50000 100000; do
  rpicam-still --raw --gain 1 --shutter $T \
    --awb off --awbgains 1,1 -o dc_t$T.dng 2>/dev/null
done

python3 - <<'EOF'
import rawpy, numpy as np
print("== read noise（短曝 1ms，σ 即 read noise）==")
for g in [1,2,4,8,16]:
    roi = rawpy.imread(f'rn_g{g}.dng').raw_image[600:1400,600:1400]
    print(f" gain={g:2d}  σ={roi.std():5.2f}")

print("== dark current（黑位均值 vs 曝光，slope=暗電流）==")
means = []
for t in [1000,10000,50000,100000]:
    m = rawpy.imread(f'dc_t{t}.dng').raw_image[600:1400,600:1400].mean()
    means.append((t,m))
    print(f" {t:6d}µs  mean={m:6.1f}")
slope = (means[-1][1]-means[0][1])/(means[-1][0]-means[0][0])
print(f" 暗電流斜率 ≈ {slope*1e6:.2f} e-/s（10-bit 單位換算）")
EOF