The largest visual area, known as the primary visual cortex or V1, has greatly contributed to the current understanding of mammalian and human visual pathways and their role in visual perception. The initial discovery of orientation-sensitive neurons in V1, arranged according to a retinotopic mapping, suggested an analogy to its function as a low-level feature analyzer. Subsequent discoveries of phase, spatial frequency, color, ocular origin, and direction-of-motion-sensitive neurons, arranged into overlapping maps, further lent support to the view that it performs a rich decomposition, similar to signal processing transforms, of the retinal output. Like the other cortical areas, V1 has a laminar organization with specialization for input from the relayed retinal afferents, output to the higher visual areas, and the segregation of the magno (motion) and parvo (form) pathways. Spatially lateral connections that exist between neurons of similar and varying properties have also been proposed to give rise to a computation of a bottom-up saliency map in V1. We provide a review of the selectivity of neurons in V1, laminar specialization and analogies to signal processing techniques, a model of V1 saliency computation, and higher-area feedback that may mediate perception.