カメラメーカーが読み出しノイズの仕様にMedianやRMSなどの単位を使う理由を理解したい方
読み出しノイズに関する用語の違いを説明します。
ノイズとCMOS技術についてさらに詳しく知りたい方は、こちらをご覧ください。Changing the Game
どのような統計的パラメータでも、データに適用できる複数のモデルがあります。読み出しノイズの計算方法としては、電気工学的に二乗平均平方根 (RMS:Root Mean Square) を定義するのが一般的です。CCDの読み出しノイズの計算には、常にこの方法が使われてきました。中央値 (Median) もRMSも統計学的に有効なモデルですが、ユーザーがカメラに期待する体験を正確に表現できるのはRMSノイズだけです。CCDの場合、すべての画素は同じ読み出し回路を経由するため、読み出しノイズの値は非常に近い値になります。そのためどちらのモデルを使うべきかという問題は発生しません。一方、sCMOSの場合は、センサの構造上画素ごとのばらつきが大きく、また、センサのノイズが極めて小さいため、画素ごとのノイズのばらつきが統計的に顕著になります。そのため、カメラの性能を評価する場合、本当に意味のあるスペックはRMSノイズになります。RMSノイズの値は、画質に対する洞察を与えるだけでなく、定量的な計算において適切なノイズ変数となります。例えば、経験的に測定したSNRが理論に合致するのは、RMSノイズ値を用いてシミュレーションを行った場合のみです。科学的画像処理において、ノイズの仕様を示すための業界標準はありませんが、仕様としての中央値ノイズは懐疑的に見て、より意味のあるRMSノイズを要求することをユーザーに勧めています。
Medianは、読み出しノイズが大きい画素の半分と、読み出しノイズが小さ画素の半分の境界値を示しており、sCMOSカメラのノイズ分布の性質上、特に参考になるものではありません。RMSは、全画素の読み出しノイズの二乗平均平方根値で、画素補正OFF時の画質を知るのに有効です。画像のSNR計算で最もよく使われる値です。
RMSまたはMedianの値は、センサの全ピクセルを使用した場合、または異常値ピクセルを除外したことが文書化され説明されている場合にのみ有効です。当社の科学用CMOSカメラでは、センサの全画素を使用してRMS読み出しノイズを算出しています。これは、画素補正機能やデータの事前検証を行うことなく行われます。スペック提供の目的の一つは、撮像結果の正確な定量化を可能にすることであり、このアプローチは、最も定量的な科学計測用カメラを提供するという我々の目標に合致しています。
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