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Abstract An adaptive decision based inverse distance weighted interpolation (DBIDWI) algorithm for the elimination of high-density salt and pepper noise in images is proposed. The pixel is initially checked for salt and pepper noise. If classified as noisy pixel, replace it with an inverse distance weighted interpolation value. This interpolation estimates the values of corrupted pixels using the distance and values nearby non-noisy pixels in vicinity. Inverse distance weighted interpolation uses the contribution of non-noisy pixel to the interpolated value. The window size is varied adaptively depending upon the non-noisy content of the current processing window. The algorithm is tested on various images and found to exhibit good results both in terms of quantitative (PSNR, MSE, SSIM, Pratt’s FOM) and qualitative (visually) at high noise densities. The algorithm performs very well in restoring an image corrupted by high-density salt and pepper noise by preserving fine details of an image.