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Blind estimation of the signal-to-noise ratio in noisy speech recordings is useful to enhance the performance of many speech processing algorithms. Most current techniques are efficient in low noise environments only, justifying the need for a high noise estimator, such as the one presented here. A pitch tracker robust in high noise was developed and is used to create a two-dimensional representation of the audio input. Signal-to-noise ratio estimation is then performed using an image processing algorithm, effectively combining the short-term and long-term properties of speech. The proposed technique is shown to perform accurately even in high noise situations.