This paper presents a computational framework inspired by the center-surround antagonistic receptive fields of the human visual system. It demonstrates that, starting from the actual pixel value (center) and a low-pass estimation of the pixel's neighborhood (surround) and using a mapping function inspired by the shunting inhibition mechanism, some widely used spatial image processing techniques can be implemented, including adaptive tone-mapping, local contrast enhancement, text binarization and local feature detection. As a result, it highlights the relations of these seemingly different applications with the early stages of the human visual system and draws insights about their characteristics.