This paper proposes a local correlation-based switching median filter for impulse noise reduction. The proposed algorithm consists of two main steps, detection and correction. In the first step, noise detection is performed using a scalable detection mask and morphological operation. In the second step, a corrupted pixel is corrected using the local correlation between the uncorrupted pixels in the mask. The experimental results showed that the proposed method can reduce impulse noise significantly and preserve more edge information than the existing state-of-art methods. In addition, the proposed method outperforms the most effective two schemes, which are simple adaptive median filter (SAM) and iterative adaptive switching median filter (IASMF) by an average of 1·68 and 0·49 dB, respectively. Therefore, we believe that the proposed method can be a useful tool for impulse noise-related products such as television, infrared-based devices and digital cameras.