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Tremendous development in Internet of Things (IoT) and mobile devices lead to several images pooled on social media websites and communicated through networking channels. These images are mostly corrupted with impulse noises due to hot pixels generated in the camera sensors and communication channels. Adaptive mean filter technique removes impulse noise at low density but is unsuccessful as noise density increases and computationally expensive. In this paper, automatic adaptive filtering technique for removal of impulse (salt and pepper) noise is demonstrated. The proposed algorithm consists of impulse noise detection and noise removal modules. An automatic impulse noise detection module is based on mean and variance technique that selects the noisy pixels among the entire image. The noise removal module is based on replacement of noisy pixel through mean and edge direction using Gabor filter. The proposed technique demonstrated better robustness compared with existing techniques.